Aaditya Ramdas

Statistics and Probability · 2014–2022

A researcher in the Science corpus: 25 papers; trusts 195 researchers and is trusted by 52 researchers here, as inferred from the citation graph.

Subfields

Statistics and Probability — 236 citations into it; #1,171 of 12,932 by trust here, #895 by citations
Artificial Intelligence — 154 citations into it; #5,376 of 35,345 by trust here, #6,569 by citations
Statistical Learning Theory — 82 citations into it; #445 of 1,038 by trust here, #409 by citations
Management Science and Operations Research — 66 citations into it; #5,097 of 11,946 by trust here, #4,746 by citations
Applied Mathematics — 31 citations into it; #6,984 of 7,620 by trust here, #4,482 by citations
Probabilistic & Bayesian Methods — 31 citations into it
Mathematical Physics — 28 citations into it
Computer Vision and Pattern Recognition — 27 citations into it; #20,542 of 21,575 by trust here, #11,721 by citations

Whom Aaditya Ramdas trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

Who trusts Aaditya Ramdas overall

Papers from Aaditya Ramdas's perspective

Ordered by how strongly the researchers Aaditya Ramdas trusts endorse each paper. Same corpus, a different order for every researcher.

ImageNet classification with deep convolutional neural networks
Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
Gradient-based learning applied to document recognition
ImageNet: A large-scale hierarchical image database
Long Short-Term Memory
Attention is All you Need (Neural Information Processing Systems)
Learning Multiple Layers of Features from Tiny Images
GENERATIVE ADVERSARIAL NETS
Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy (2016) — 293 citations
On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions (2014) — 215 citations
Conformal Prediction Under Covariate Shift (2019) — 742 citations
Fast Two-Sample Testing with Analytic Representations of Probability Measures (2015) — 169 citations
The limits of distribution-free conditional predictive inference (2019) — 376 citations
A unified treatment of multiple testing with prior knowledge using the p-filter (2017) — 112 citations
On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives (2015) — 40 citations
Predictive inference with the jackknife+ (2019) — 442 citations
Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing (2015) — 48 citations
On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives (2014) — 9 citations
Fast and Flexible ADMM Algorithms for Trend Filtering (2014) — 130 citations
On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests (2015) — 613 citations
Time-uniform, nonparametric, nonasymptotic confidence sequences (2018) — 383 citations
Classification Accuracy as a Proxy for Two Sample Testing (2016) — 95 citations
Estimating means of bounded random variables by betting (2020) — 274 citations
Time-uniform Chernoff bounds via nonnegative supermartingales (2018) — 220 citations
Admissible anytime-valid sequential inference must rely on nonnegative martingales. (2020) — 150 citations
Nonparametric Independence Testing for Small Sample Sizes (2014) — 14 citations
False discovery rate control with e‐values (2020) — 174 citations
Sequential estimation of quantiles with applications to A/B testing and best-arm identification (2019) — 73 citations