← Authors

Danica J. Sutherland

31 papers · 2015–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (10) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) 🐝 Cross-Pollinator (11) πŸ—ΊοΈ Taxonomy Completionist (10) πŸ‘₯ Mega-Team (22) πŸ‘‘ Triple Crown πŸ—ƒοΈ Keyword Collector (106) ⚑ Prolific Year (6) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ’Ž Century Club (31) πŸ”₯ Unstoppable (8) ❓ The Questioner

Conferences

NIPS (11) ICLR (6) ICML (5) AISTATS (4) ECCV (3) IJCAI (1) JMLR (1)

Top co-authors

Wonho Bae (8) Arthur Gretton (7) Yi Ren (5) Mohamad Amin Mohamadi (3) Michael Arbel (3) Hamed Shirzad (3) Lijia Zhou (3) Junhyug Noh (3) Shangmin Guo (3) Feng Liu (2)

Research topics

Probability (1)

Keywords

kernel methods (4) generalization bound (3) maximum mean discrepancy (3) graph neural network (2) interpolation learning (2) neural tangent kernel (2) graph transformer (2) active learning (2) representation learning (2) deep neural network (2) iterated learning (2) deep kernel (2) contrastive learning (2) bayesian inference (2) density estimation (2) uniform convergence (2) score matching (2) linear regression (2) sparse attention (2) transfer learning (1)

Papers

Uncertainty Herding: One Active Learning Method for All Label Budgets ICLR 2025
Learning Dynamics of LLM Finetuning ICLR 2025
Bias Amplification in Language Model Evolution: An Iterated Learning Perspective NIPS 2024
Even Sparser Graph Transformers NIPS 2024
Why Do You Grok? A Theoretical Analysis on Grokking Modular Addition ICML 2024
Generalized Coverage for More Robust Low-Budget Active Learning ECCV 2024
Exploring Active Learning in Meta-Learning: Enhancing Context Set Labeling ECCV 2024
A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel ICML 2023
MMD-B-Fair: Learning Fair Representations with Statistical Testing AISTATS 2023
Efficient Conditionally Invariant Representation Learning ICLR 2023
Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings NIPS 2023
How to prepare your task head for finetuning ICLR 2023
Exphormer: Sparse Transformers for Graphs ICML 2023
Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels NIPS 2022
Better Supervisory Signals by Observing Learning Paths ICLR 2022
Object Discovery via Contrastive Learning for Weakly Supervised Object Detection ECCV 2022
One Weird Trick to Improve Your Semi-Weakly Supervised Semantic Segmentation Model IJCAI 2022
Evaluating Graph Generative Models with Contrastively Learned Features NIPS 2022
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models NIPS 2022
POT: Python Optimal Transport JMLR 2021
Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data NIPS 2021
Self-Supervised Learning with Kernel Dependence Maximization NIPS 2021
Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds and Benign Overfitting NIPS 2021
Learning Deep Kernels for Non-Parametric Two-Sample Tests ICML 2020
On Uniform Convergence and Low-Norm Interpolation Learning NIPS 2020
Learning deep kernels for exponential family densities ICML 2019
On gradient regularizers for MMD GANs NIPS 2018
Bayesian Approaches to Distribution Regression AISTATS 2018
Efficient and principled score estimation with NystrΓΆm kernel exponential families AISTATS 2018
Demystifying MMD GANs ICLR 2018
Active Pointillistic Pattern Search AISTATS 2015