{"list":"other","total":61,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"2005.14165","title":"Language Models are Few-Shot Learners","created":"2020-05-28","cited_by_count":32419},{"id":"1912.01703","title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","created":"2019-12-03","cited_by_count":20305},{"id":"1703.06870","title":"Mask R-CNN","created":"2017-03-20","cited_by_count":7277},{"id":"1603.02754","title":"XGBoost: A Scalable Tree Boosting System","created":"2016-03-09","cited_by_count":5166},{"id":"1602.04938","title":"\"Why Should I Trust You?\": Explaining the Predictions of Any Classifier","created":"2016-02-16","cited_by_count":5070},{"id":"1806.07366","title":"Neural Ordinary Differential Equations","created":"2018-06-19","cited_by_count":3779},{"id":"1903.02428","title":"Fast Graph Representation Learning with PyTorch Geometric","created":"2019-03-06","cited_by_count":2434},{"id":"1803.03635","title":"The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks","created":"2018-03-09","cited_by_count":2262},{"id":"1910.03771","title":"HuggingFace's Transformers: State-of-the-art Natural Language Processing","created":"2019-10-09","cited_by_count":2218},{"id":"1610.02413","title":"Equality of Opportunity in Supervised Learning","created":"2016-10-07","cited_by_count":2007},{"id":"1910.10045","title":"Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI","created":"2019-10-22","cited_by_count":1552},{"id":"2012.07421","title":"WILDS: A Benchmark of in-the-Wild Distribution Shifts","created":"2020-12-14","cited_by_count":1375},{"id":"1911.02685","title":"A Comprehensive Survey on Transfer Learning","created":"2019-11-07","cited_by_count":1160},{"id":"1912.06680","title":"Dota 2 with Large Scale Deep Reinforcement Learning","created":"2019-12-13","cited_by_count":1103},{"id":"1608.07187","title":"Semantics derived automatically from language corpora contain human-like biases","created":"2016-08-25","cited_by_count":901},{"id":"1705.07057","title":"Masked Autoregressive Flow for Density Estimation","created":"2017-05-19","cited_by_count":684},{"id":"1912.02292","title":"Deep Double Descent: Where Bigger Models and More Data Hurt","created":"2019-12-04","cited_by_count":672},{"id":"1908.07442","title":"TabNet: Attentive Interpretable Tabular Learning","created":"2019-08-20","cited_by_count":648},{"id":"1907.10597","title":"Green AI","created":"2019-07-22","cited_by_count":627},{"id":"1510.04342","title":"Estimation and Inference of Heterogeneous Treatment Effects using Random Forests","created":"2015-10-14","cited_by_count":600},{"id":"1904.11955","title":"On Exact Computation with an Infinitely Wide Neural Net","created":"2019-04-26","cited_by_count":573},{"id":"1904.05046","title":"Generalizing from a Few Examples: A Survey on Few-Shot Learning","created":"2019-04-10","cited_by_count":463},{"id":"1905.13655","title":"Implicit Regularization in Deep Matrix Factorization","created":"2019-05-31","cited_by_count":405},{"id":"2001.04385","title":"Universal Differential Equations for Scientific Machine Learning","created":"2020-01-13","cited_by_count":353},{"id":"2104.00954","title":"Skillful Precipitation Nowcasting using Deep Generative Models of Radar","created":"2021-04-02","cited_by_count":311},{"id":"2104.02395","title":"Ensemble deep learning: A review","created":"2021-04-06","cited_by_count":284},{"id":"1812.10352","title":"Learning Not to Learn: Training Deep Neural Networks with Biased Data","created":"2018-12-26","cited_by_count":255},{"id":"2010.15327","title":"Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth","created":"2020-10-29","cited_by_count":245},{"id":"1911.10500","title":"Causality for Machine Learning","created":"2019-11-24","cited_by_count":243},{"id":"1612.08468","title":"Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models","created":"2016-12-27","cited_by_count":213},{"id":"2002.06470","title":"Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning","created":"2020-02-15","cited_by_count":210},{"id":"1804.03142","title":"Markerless tracking of user-defined features with deep learning","created":"2018-04-09","cited_by_count":206},{"id":"1805.08522","title":"Deep learning generalizes because the parameter-function map is biased towards simple functions","created":"2018-05-22","cited_by_count":183},{"id":"1508.04409","title":"ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R","created":"2015-08-18","cited_by_count":172},{"id":"2103.10427","title":"The Low-Rank Simplicity Bias in Deep Networks","created":"2021-03-18","cited_by_count":154},{"id":"2012.09839","title":"Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning","created":"2020-12-17","cited_by_count":150},{"id":"1912.02803","title":"Neural Tangents: Fast and Easy Infinite Neural Networks in Python","created":"2019-12-05","cited_by_count":149},{"id":"2110.12951","title":"Seeing biodiversity: perspectives in machine learning for wildlife conservation","created":"2021-10-25","cited_by_count":130},{"id":"1907.06890","title":"A General Framework for Uncertainty Estimation in Deep Learning","created":"2019-07-16","cited_by_count":119},{"id":"1809.02169","title":"Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings","created":"2018-09-06","cited_by_count":114},{"id":"2002.11328","title":"Rethinking Bias-Variance Trade-off for Generalization of Neural Networks","created":"2020-02-26","cited_by_count":107},{"id":"2111.13171","title":"Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks","created":"2021-11-25","cited_by_count":70},{"id":"2002.04806","title":"The Unreasonable Effectiveness of Deep Learning in Artificial Intelligence","created":"2020-02-12","cited_by_count":57},{"id":"1906.03728","title":"The Generalization-Stability Tradeoff In Neural Network Pruning","created":"2019-06-09","cited_by_count":54},{"id":"2201.04600","title":"Deep Symbolic Regression for Recurrent Sequences","created":"2022-01-12","cited_by_count":54},{"id":"1811.01457","title":"Fashionable Modelling with Flux","created":"2018-11-01","cited_by_count":53},{"id":"1912.03538","title":"Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection","created":"2019-12-07","cited_by_count":45},{"id":"1807.05812","title":"Automatic acoustic detection of birds through deep learning: the first Bird Audio Detection challenge","created":"2018-07-16","cited_by_count":44},{"id":"1910.09716","title":"A deep active learning system for species identification and counting in camera trap images","created":"2019-10-22","cited_by_count":44},{"id":"2109.04173","title":"Relating Graph Neural Networks to Structural Causal Models","created":"2021-09-09","cited_by_count":41},{"id":"2005.07939","title":"Predicting into unknown space? Estimating the area of applicability of spatial prediction models","created":"2020-05-16","cited_by_count":29},{"id":"2107.10400","title":"Species Distribution Modeling for Machine Learning Practitioners: A Review","created":"2021-07-03","cited_by_count":21},{"id":"2010.07143","title":"A Graph Neural Network Framework for Causal Inference in Brain Networks","created":"2020-10-14","cited_by_count":16},{"id":"1911.09189","title":"Information in Infinite Ensembles of Infinitely-Wide Neural Networks","created":"2019-11-20","cited_by_count":14},{"id":"2110.05667","title":"Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks","created":"2021-10-12","cited_by_count":14},{"id":"2103.06002","title":"Robustness to Pruning Predicts Generalization in Deep Neural Networks","created":"2021-03-10","cited_by_count":10},{"id":"1803.08591","title":"End-to-End Learning for the Deep Multivariate Probit Model","created":"2018-03-22","cited_by_count":8},{"id":"2202.02124","title":"TIML: Task-Informed Meta-Learning for Agriculture","created":"2022-02-04","cited_by_count":7},{"id":"1908.09853","title":"Machine learning algorithms to infer trait-matching and predict species interactions in ecological networks","created":"2019-08-26","cited_by_count":4},{"id":"2108.06415","title":"The Sharpe predictor for fairness in machine learning","created":"2021-08-13","cited_by_count":2}],"next_cursor":null}