Top 10 most important machine learning papers

Top 10 most important machine learning papers. Machine learning research has brought about tangible changes in our daily lives. How to read a Research Paper. They should be related to fewer researchers and articles in these directions. Specifically, we apply a topic coherence model with latent Dirichlet allocation (LDA) to evaluate the optimal number of topics and significant topics for a dataset. Sep 22, 2021 · Therefore, in this paper, we propose a method to identify the trends in machine learning research based on significant topics over time automatically. Friends: find a community or a group of friends ,interested in the field, that shares interesting research papers. Neal (1993). Paper. Machine Translation and “Multilinguality” (Multilingualism) Interpretability and Analysis of Models for NLP. This is a list of 100 important natural language processing (NLP) papers that serious students and researchers working in the field should probably know about and read. Mar 5, 2020 · ACL 2020: Association for Computational Linguistics. This article summarizes some of the most important LLM papers published during the third week of December. Apr 18, 2021 · This is one of the keys, along with the open culture, of Machine Learning that has allowed the field to develop at the rate it is going in recent years. one of the most prestigious conferences on machine learning, is an important Jan 13, 2023 · This 2022 ML paper presents an algorithm that teaches the meta-learner how to overcome the meta-optimization challenge and myopic meta goals. CL, cs. Jun 3, 2017 · Learning and transferring mid-Level image representations using convolutional neural networks (2014), M. Trying to keep up with AI research papers can feel like an exercise in futility given how quickly the industry moves. The event gathers top researchers from academia, tech giants, and startups that May 1, 2019 · Natural Language Processing (NLP) is not a machine learning method per se, but rather a widely used technique to prepare text for machine learning. 4%, and specificity of 73. io. View on GitHub mlpapers/mlpapers. Dec 8, 2020 · This list is also Slator’s way of bidding adieu to the “neural” in neural machine translation, as most of the industry now refers to NMT as simply MT. Masters in machine learning graduates are at the Apr 29, 2023 · Machine-learning-based text classification is one of the leading research areas and has a wide range of applications, which include spam detection, hate speech identification, reviews, rating summarization, sentiment analysis, and topic modelling. Figure 1. In this paper, the Facebook AI Research team presents a simple, yet flexible framework for object instance segmentation. Analysis and Detection of Autism Spectrum Disorder Using Machine Learning Techniques. Some might contend that many of these older methods fall into the camp of ‘statistical analysis' rather than machine learning, and prefer to date [] Many basic details are omitted which readers are expected to infer. AI, a branch of computer science, encompasses mathematical methods that enable the decision making or action, the rational and autonomous reasoning, and the effective adaptation to complex and unseen situations . 2. Masked Autoencoder pipeline. If a paper is added to the list, another paper (usually from *More Papers from 2016" section) should be removed to keep top 100 papers. The papers are split by topic and indicated which Jun 3, 2022 · Figure 1. However, this surge in performance, has often been achieved through increased model complexity, turning such systems into “black box Jan 4, 2024 · Here are the top 10 AI and machine learning trends to prepare for in 2024. Below are the top-10 most impactful research papers published in top AI conferences during the last 5 years. Mar 29, 2020 · Feature importance refers to techniques that assign a score to input features based on how useful they are at predicting a target variable. Multimodal AI. 54% on the testing data while the DT gained an accuracy of 76. To do this, we plot data items as points in n-dimensional space, where n is the number of input features. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. The International Joint Conference on NEural Networks (IJCNN) covers a wide range of topics in the field of neural networks, from biological neural networks to artificial neural computation. The year 2019 saw an increase in the number of submissions. CL is only about half the Apr 12, 2021 · Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition Sep 9, 2018 · Every week new deep learning papers are published, which often build on previous papers (the normal path in science). Aug 23, 2023 · When: 18-22 July, 2021. 2014: SPPNet. The full top-100 list for 2022 is included below in this post. Top 10 machine learning & AI research papers of 2018; Top 10 AI fairness, accountability, transparency, and ethics (FATE) papers of 2018 Dec 11, 2023 · As new generations of models are developed, it’s important for researchers and engineers to stay informed on the latest progress. — This paper introduced the Bidirectional Encoder Sep 24, 2020 · We’ll wrap things up with a survey so that you can see what the community thinks is the most important topic out of this group of papers. The papers cover various topics shaping the next Sep 14, 2023 · In exploring 10 Reasons Why Machine Learning Is Important, we’ll uncover this discipline’s pivotal role in shaping our future. Machine Learning, 20, 273-297, 1995. Voice assistants like Siri and Alexa, recommendation systems on streaming platforms, and personalized healthcare diagnostics are just a few examples of how this research impacts our world. 1. It includes the following steps: Pick a topic of your interest (e. The structure is usually common in most papers but it can vary in the different fields of study. Oquab et al. Widely used machine-learning-based research differs in terms of the datasets, training methods, performance evaluation, and comparison methods used International Scientific Journal & Country Ranking. Compile a list of 10–20 papers/articles/blog posts. We curate a dataset of 123 milestone Machine Learning systems, annotated with the compute it took to train them. Supervised Algorithms: data is labeled and the algorithm learns to predict the output from input data. , Learning long-term dependencies with gradient descent is difficult. N. We used feature importance based on the mean decrease in impurity Apr 20, 2020 · 5. Aug 14, 2023 · The five most frequent fine-grained categories are cs. (Thus, removing papers is also important contributions as well as adding papers) Jan 13, 2023 · Panda Data frame: Pandas is a Python data manipulation library that is both powerful and flexible. Where: Virtual only. If you’re buried in papers to read that you haven’t quite gotten around to, you’re in luck. Code. Reinforcement Learning & More. SVM tries to draw two lines between the data points with the largest margin between them. Jul 31, 2022 · Each sub-layer of the transformers in the Attention paper is wrapped by a skip-layer, or a residual-block (see image below). [pdf] Read the full list here . There is a great deal of misunderstanding about what machine learning is, fueled by recent success and at times sensationalist media coverage. Improvement of the Recognition Rate by Random Forest. This list is compiled by Masato Hagiwara. Quoted times: 33540. ·. Linear regression is a supervised machine learning technique used for predicting and forecasting values that fall within a continuous range, such as sales numbers or housing prices. Khan. 97%, sensitivity of 78. Mar 13, 2023 · 3. There are many types and sources of feature importance scores, although popular examples include statistical correlation scores, coefficients calculated as part of linear models, decision trees, and permutation importance scores. Get Help. We offer estimates of the doubling times during each of these eras. Image retrieved from original paper. 3 pass approach to read a research paper. Over the lifetime, 2466 publication (s) have been published in the journal receiving 349540 citation (s). AI Hub from Google is the first place where you can start. Automating decision-making processes is a pivotal aspect of why machine learning holds immense significance today. We tentatively frame the trends in compute in terms of three distinct eras: the Pre Deep Learning Era , the Deep Learning Era and the Large-Scale Era . S. Dec 21, 2023 · Large language models (LLMs) have advanced rapidly in recent years. It is a near-20 year algorithm in the machine learning lakes. Also: please for the love of god use already known theorems, like all the classical stochastics. 5. github. R. Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents. Contribute to daturkel/learning-papers development by creating an account on GitHub. The fact that R 2 is subtracting a set {0, 0} instead of the set containing the pair { (0,0)} is wrong from the perspective of set theory. Computer Vision. To help [] Feb 14, 2023 · Here are the top 10 research papers on deep learning, each with a brief description and example of the theme of the paper: of the most important contributions to deep learning in recent years Aug 1, 2020 · If you like to keep learning this area, I’ve also listed some other interesting papers to read. The final sections discuss papers related to training LLMs safely Jan 6, 2022 · Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets. Latent Dirichlet Allocation (available full-text) LDA is a means of classifying objects, such as documents, based on their underlying topics. We have proven optimal solutions for some topics. 4K votes, 36 comments. Decision Tree algorithm in machine learning is one of the most popular algorithm in use today; this is a supervised learning algorithm that is used for classifying problems. Think of tons of text documents in a variety of formats (word, online blogs, . The algorithm’s primary objective is meta-learning using gradients, which ensures improved performance. Eh, it is not bizarre, just shorthand. Stable Diffusion 🎨 creates hyperrealistic art. The papers cover various topics shaping the next generation of language models, from model optimization and scaling to reasoning, benchmarking, and enhancing performance. Temporal Difference Models: Model-Free Deep RL for Model-Based Control. Machine learning research papers showcasing the transformation of the technology. Step 1: Assembling all available resources. The most popular explanation technique is feature importance. 3,769. It represents the linear model, the hill of nuclear skills, this is the official text of the SVM. I mean a research paper can be abstract to new readers but seductive since the new readers are very interested (and somewhat overzealous) to the topic, but ended getting demotivated due to not understanding the paper - and not necessarily it's because they aren't capable of understanding the paper; maybe it's the paper's style of writing Feb 24, 2023 · Here are the top 10 Deep Learning papers published in 2018 available on arxiv. May 22, 2020 · Here, we provide you with our list of Top 10 Most Cited Machine Learning Articles based on info in CiteSeer database as of 19 March 2015. speech recognition, text summarization, image generation with GANs). Jul 31, 2021 · Dynamically Expanding field of Deep Learning. A data scientist can use DataFrames to perform a variety of data manipulation tasks, such as filtering, aggregation, and group-by operations, as well as handle missing values and perform data cleaning tasks. #1 — Hidden Technical Debt in Machine Learning Systems 🙈. Sep 9, 2022 · Figure 5 illustrates the top-10 most important features or variables based on the random forest algorithm with the SFM optimiser. #1 Neural Machine Translation by Jointly Learning to Align and Translate. Probabilistic inference using Markov chain Monte Carlo methods. Ng shares a simple and quite effective technique for planning your reading. November 24, 2020 by Mariya Yao. One of the best tutorial papers on machine learning ever written, in my opinion. Keys to Simplify the Read of a Scientific Paper Paper’s Structure. ML (statistics, machine learning) and cs. The Mask R-CNN framework for instance segmentation. It might feel embarrassing if the code is messy but we all have our flaws. on each paragraph of the paper. Although not included in the top-10 list, these papers are all famous in their own area and inspired many other researchers in the world. The research paper also examines the potential benefits due to bootstrapping. Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption, with machine learning systems demonstrating superhuman performance in a significant number of tasks. Paper Digest Team analyze all papers published on ICML in the past years, and presents the 10 most influential papers for each year. Pandas Series: It is a useful tool for To help you quickly get up to speed on the latest ML trends, we’re introducing our research series, in which we curate the key AI research papers of 2019 and summarize them in an easy-to-read bullet-point format. The most important reason for this recommendation with ML & AI workloads is the number of PCI-Express lanes that these CPUs support, which will dictate how many GPUs can be utilized. Here are the 20 most important (most-cited) scientific papers that have been published since 2014, starting with "Dropout: a simple way to prevent neural networks from overfitting". Zeiler and R. ). Machine Learning , Python , Business Forecasting , Algorithmic Trading. [pdf] Visualizing and understanding convolutional networks (2014), M. It is a bit strange that the support vector machine is ranked to the 10 position. Artificial Intelligence (AI) has recently made eminent progress in many areas, including medicine and biomedical research. Yeah, this is soo true. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of analytical model building and solve associated tasks. 78%. Feature importance [] Sep 17, 2019 · As we have in past years, Two Sigma sponsored the ICLR 2021, which took place virtually in May. Mar 22, 2021 · A successful machine learning model depends on both the data and the performance of the learning algorithms. The team at Google Research provides clear instructions on antipatterns to avoid when setting up your data science workflow. However, machine learning theoretical articles, as a whole, have relatively few citations. Synopsis: Statistical learning theory was introduced in the late 1960’s. This year, we see significant progress in the field of generative models. Feb 9, 2024 · use a non-linear model. Example of the random notebook from AI Hub. Aug 9, 2019 · Important Machine Learning Conferences: NIPS/ICML/ICLR. You can also search in GitHub and Kaggle for the paper implementation. This list is originally based on the answers for a Quora question I posted years ago: What are the Dec 3, 2021 · DTs and LR are among the ones that are most used. Therefore, it is essential to get a good overview of some entry points to the Mar 20, 2021 · Interpretability in machine learning (ML) is crucial for high stakes decisions and troubleshooting. Feb 11, 2019 · If you’d like to skip around, here are the papers we featured: Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor. IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures. August 23, 2021. Welcome to the January edition of the ‚Machine-Learning-Collage‘ series, where I provide an overview of the different Deep Learning research streams. Feb 3, 2021 · Explainable artificial intelligence is an emerging research direction helping the user or developer of machine learning models understand why models behave the way they do. The idea behind this block is that given an input x, a network tries to learn some function H (x), which can be loosely written as H (x) = F (x) + x. Cortes, C. Just skim such books and find those important references you need. Literature survey of a domain. Introduction. Nov 27, 2018 · UPDATE: We’ve also summarized the top 2019 and top 2020 AI & machine learning research papers. If you are following deep learning techniques for a while, you have probably heard of BERT, a self-supervised technique used in languages where you mask out part of sentences for pretraining for the betterment of learning implicit representations. Two are genetics papers. May 25, 2020 · 1. Donahue et al. Author: V Vapnik in 1998. Source: Zeta Alpha. Linear regression. g. LG, cs. When you read a paper, you never read it only once. Date Published: September 2014. Feb 8, 2024 · Top Machine Learning Project with Source Code [2024] We mainly include projects that solve real-world problems to demonstrate how machine learning solves these real-world problems like: – Online Payment Fraud Detection using Machine Learning in Python, Rainfall Prediction using Machine Learning in Python, and Facemask Detection using Mar 8, 2021 · Mar 8, 2021. The papers cover various topics shaping the next generation of language models, from model optimization Jan 9, 2022 · 7 min read. “Human-Robot Collaboration: AI’s Role in Robotics” by Dr. Nov 9, 2023 · 9. May 6, 2011 · 1. Jan 21, 2018 · To associate your repository with the machine-learning-papers topic, visit your repo's landing page and select "manage topics. For many applications, deep Nov 24, 2020 · The Best of Applied Artificial Intelligence, Machine Learning, Automation, Bots, Chatbots. GPT-3 by OpenAI may be the most famous, but there are Machine learning and Deep Learning research advances are transforming our technology. 10. In this paper we propose to study generalization of neural networks on small algorithmically generated datasets. The predicted output of the neural network is compared with the actual output. Most of these text documents will be full of typos, missing characters and other words that needed to be filtered out. It's an excellent, important paper. 2020’s Top AI & Machine Learning Research Papers. Using the skip-layer mechanism, we force the middle layer to learn F (x Jan 18, 2024 · 5. These were the Top 10 themes in this year’s conference. 12. 4 mins read. This ranking list is automatically constructed based upon Dec 29, 2022 · Dec 29, 2022. A few Asian countries, such as China, India and Singapore, were listed in the top 10 countries based on the total citation. In this work, we provide fundamental principles for interpretable ML, and dispel common misunderstandings that dilute the importance of this crucial topic. writing 1D constants, a, b, as a pair (a,b) in R2 is simply bizarre. Oct 6, 2021 · 1. His most influential achievement is support vector machine, VC dimension. Landmark Papers in Machine Learning. There's a famous paper by Bengio et al. But perhaps the main advantage of this resource is a large number of Google Colab notebooks that demonstrate the functioning or training process of some models. To understand the math in Aug 13, 2019 · Prof. Collection of open machine learning papers. network, the output of the input is already known. Each and every book about ML and deep learning has some important references to papers. Feb 2, 2022 · Another recent paper at the intersection of Reinforcement Learning and Language Models that could be interesting is Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents. A special thanks to Alexandre Passos for his comment on this Reddit thread, as well as the responders to this Quora post. We also identify 10 technical challenge areas in interpretable machine learning and provide history and background on each problem. Rodriguez. Until the 1990’s it was a purely theoretical analysis of Oct 9, 2022 · Here is how you can approach this: 1. The neat thing is this doesn't really matter: the overall results are generally right. Here are the topics we cover: Natural Language Processing & Conversational AI. Machine Learning for NLP. Decision Tree. As new generations of models are developed, researchers and engineers need to stay informed on the latest progress. Nov 18, 2021 · Machine learning and deep learning have accomplished various astounding feats this year in 2021, and key research articles have resulted in technical advances used by billions of people. You read the title first, than you decide if you should read the abstract. Feb 9, 2024 · From classification to regression, here are 10 types of machine learning algorithms you need to know in the field of machine learning: 1. ChatGPT 💬 answers questions to the meaning of life. Statistical Learning Theory. 54%, sensitivity of 79. This paper discusses the latest strides in natural language processing, highlighting the evolution of contextual language models for nuanced text understanding and generation. A list of top 100 deep learning papers published from 2012 to 2016 is suggested. Feb 11, 2021 · Most Influential ICML Papers (2021-02) The International Conference on Machine Learning (ICML) is one of the top machine learning conferences in the world. It works well in classifying both categorical and continuous dependent variables. Step2 - Filtering out relevant and Irrelevant resources. Here you can find datasets, pretrained models, and much more. Tackling COVID-19 with AI & Machine Learning. Event dates: July 5–10, 2020. Dec 19, 2019 · The artificial intelligence sector sees over 14,000 papers published each year. So what is a ML collage? Simply put, I draft one-slide visual summaries of one of my favourite recent papers. The journal publishes majorly in the area (s): Computer science & Artificial intelligence. Why to read research Papers. Support vector networks. 30 stars / hour. While its applications have been and will continue to be extraordinarily powerful under the right circumstances, it’s important to gain some sense of where and why the tools presented in this book will A "math heavy paper" could mean: a paper with long equations, lots of algebra and manipulation of complicated equations. Jan 24, 2019 · Due to popular demand, we’ve released several of these easy-to-read summaries and syntheses of major research papers for different subtopics within AI and machine learning. The complete-background list: the full list, containing all of the papers that anyone who wants to perform neural network evaluations should read. Follow on Twitter @mlpapers. This field attracts one of the most productive research groups globally. Information Extraction. Aug 23, 2021 · Arti. It’s one of the most popular conferences on machine learning. Fergus [pdf] Decaf: A deep convolutional activation feature for generic visual recognition (2014), J. Check the availability of the paper data and code: Have a look at the paper with the code website and see whether the code and the data of this paper are available or not. Jul 13, 2020 · Three of the top five papers listed by Google Scholar for Nature are related to AI. MobileNetV1-Based Deep Learning Model for Accurate Brain Tumor Classification. I welcome any feedback on this list. The ranking is based on the number of citations and We would like to show you a description here but the site won’t allow us. You read the abstract and decide if you will skim through the results. May 13, 2020 · Both papers are listed below: Learning to Reinforcement Learn (2016) - Jane X Wang et al. Gradually expand this list to 50+ papers. Paper Submission Deadline: December 9, 2019. We’ll start with the top 10 AI research papers that we find important and representative of the latest research trends. --. A Machine Learning-Based Recommender System for Improving Students Learning Experiences. . org, ranked by the number of citations they received (as of my knowledge cutoff date of September 2021): “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding” by Jacob Devlin et al. Each year scientists from around the world publish thousands of research papers in AI but only a few of them reach wide audiences and make a global impact in the world. ACL is the key conference in the area of computational linguistics and natural language processing (NLP). Memorization. Jul 15, 2018 · The quick-introduction list: the ~10 most important papers to read to get a solid grounding in the field of adversarial examples in machine learning. Automation of Decision-Making Processes. Here is a collection of the most important recent scientific study Feb 2, 2019 · The only theoretical article in the Top 10 is from Vapnik. CV (computer vision), stat. Conclusion: Various countries demonstrated comparable interest in breast cancer and machine-learning research. Location: Seattle, WA, USA. Citations: 9898. 11%, and specificity of 75. Jan 9, 2022. The research in this sector is advancing at a breakneck pace and assisting you to keep up. These points are addressed in seven proof-of-concept experiments, each of which Find the latest published documents for machine learning, Related hot topics, top authors, the most cited documents, and related journals Nov 5, 2023 · This article summarizes some of the most important LLM papers published during the second week of October. In this study we compare different Mar 4, 2022 · Ten clusters were identified as both basic and specialised themes of breast cancer and machine learning. “Advancements in NLP: Contextual Understanding in Language Models” by Prof. In 2021, machine learning and deep learning had many amazing advances and important research papers may lead to breakthroughs in technology that get used by billions of people. However, there are several different approaches how feature importances are being measured, most notably global and local. They provided many great papers to get this list off to a great start. Unsupervised Algorithms: data is unlabeled and the algorithm learns the inherent structure from the input data. In this paper; we introduce a system of automatic recognition of characters based on the Random Forest Method in non-constrictive pictures that are stemmed from the terminals Mobile phone. I was surprised to see this paper as number one instead of Shannon’s information theory paper (#7) or the paper describing the concept that became Google (#3). Apr 30, 2022 · AI Hub. This article summarizes some of the most important LLM papers published during the fourth week of November. Step3: Taking Systematic Notes. But from a pedantic point of view, some of the mathematical definitions and arguments make no sense at all. ICLR and similar conferences, such as ICML and NeurIPS, showcase the cutting edge in machine learning and related fields, such as statistics, data science, and robotics. cs. " GitHub is where people build software. SCImago Institutions Rankings SCImago Media Rankings SCImago Iber SCImago Research Centers Ranking SCImago Graphica Ediciones A unifying review of linear-Gaussian models. Concerns unsupervised learning with linear parameterizations. Abstract. Some of Real-world Applications. 363K subscribers in the learnmachinelearning community. The sophisticated learning algorithms then need to be trained through the collected real-world data and knowledge related to the target application before the system can assist with intelligent decision-making. “In just the last five or 10 years, machine learning has become a critical way, arguably the most important way, most parts of AI are done,” said MIT Sloan professor. Feb 10, 2022 · Though we're living through a time of extraordinary innovation in GPU-accelerated machine learning, the latest research papers frequently (and prominently) feature algorithms that are decades, in certain cases 70 years old. Organization of a Paper. Multimodal AI goes beyond traditional single-mode data processing to encompass multiple input types, such as text, images and sound -- a step toward mimicking the human ability to process diverse sensory information. AI (artificial intelligence). and Vapnik, V. Support Vector Machines (SVM) SVM is a supervised algorithm used for classification problems. via Oreilly This year [] PanTheRiceMan. Dec 1, 2020 · Our team reviewed the papers accepted to NeurIPS 2020 and shortlisted the most interesting ones across different research areas. This paper unpacks two key talking points, the limitations of sparse training data, and also if recurrent networks can support meta-learning in a fully supervised context. Jun 6, 2022 · The 60th Annual Meeting of the ACL took place from May 22–27, 2022 as a hybrid event, in Dublin and online. Explore 66 research articles published in the Journal Machine Learning (Springer Science+Business Media) in the year 2023. Overall, the DT model performed better than the LR model. AI conferences like NeurIPS, ICML, ICLR, ACL and MLDS, among others, attract scores of interesting papers every year. Every paper should come with code. Citations: ≈14,400. For example the latest Sebastian Raschka book from 2022 about Machine Learning is very good and cites milestones paper. openai/grok • • 6 Jan 2022. Both Intel Xeon W-3300 and AMD Threadripper PRO 7000 Series support enough PCIe lanes for three or four GPUs (depending on motherboard layout, chassis space, and There are basically three types of artificial neural network: supervised, unsupervised and reinforcement. LR achieved a ACC of 76. Bake them into your nets. Bringing together academics, industry practitioners, entrepreneurs, and more Apr 21, 2021 · Machine learning is a subfield of artificial intelligence that gives computers the ability to learn without explicitly being programmed. Deep learning is a machine learning concept based on artificial neural networks. 3. By working on new research topics, scientists can Jan 11, 2024 · Project Topics. Mar 2, 2023 · The United States and Google still dominate, and DeepMind has had a stellar year of success, but given its volume of output, OpenAI is really in a league of its own both in product impact, and in research that becomes quickly and broadly cited. Galactica 🧬 learns humanity’s scientific knowledge but also reveals the limitations of large language models. Mask R-CNN – One of the highest-rated CNN papers on Papers With Code, Mask R-CNN achieved a SOTA (state of the art) rating for the Instance Segmentation on Cityscapes test. •. Despite the challenges of 2020, the AI research community produced a number of meaningful technical breakthroughs. ou ko uk rr wg es qm xd xm is