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Kevin Swersky · SciRah

Researcher profile · Semantic Scholar

Kevin Swersky

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Kevin Swersky — researcher profile on SciRah

h-index: 24
Works: 51
Citations: 26K

Most-cited papers

Prototypical Networks for Few-shot Learning
Jake Snell, Kevin Swersky, R. Zemel
2017Neural Information Processing Systems11K citations
Semantic Scholar
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, N. Savinov, Denis Teplyashin, Dmitry Lepikhin +496 more
2024arXiv.org4,129 citations
Semantic Scholar
Learning Fair Representations
R. Zemel, Ledell Yu Wu, Kevin Swersky, T. Pitassi +1 more
2013International Conference on Machine Learning2,086 citations
Semantic Scholar
Meta-Learning for Semi-Supervised Few-Shot Classification
Mengye Ren, Eleni Triantafillou, S. Ravi, Jake Snell +4 more
2018International Conference on Learning Representations1,467 citations
Semantic Scholar
Scalable Bayesian Optimization Using Deep Neural Networks
Jasper Snoek, Oren Rippel, Kevin Swersky, R. Kiros +5 more
2015International Conference on Machine Learning1,169 citations
Semantic Scholar
Generative Moment Matching Networks
Yujia Li, Kevin Swersky, R. Zemel
2015International Conference on Machine Learning967 citations
Semantic Scholar
Multi-Task Bayesian Optimization
Kevin Swersky, Jasper Snoek, Ryan P. Adams
2013Neural Information Processing Systems869 citations
Semantic Scholar
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
Eleni Triantafillou, Tyler Lixuan Zhu, V. Dumoulin, P. Lamblin +7 more
2019International Conference on Learning Representations714 citations
Semantic Scholar
The Variational Fair Autoencoder
Christos Louizos, Kevin Swersky, Yujia Li, M. Welling +1 more
2015International Conference on Learning Representations691 citations
Semantic Scholar
Directly Fine-Tuning Diffusion Models on Differentiable Rewards
Kevin Clark, Paul Vicol, Kevin Swersky, David J. Fleet
2023International Conference on Learning Representations509 citations Open access
Semantic Scholar
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models
Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand +37 more
2023Trans. Mach. Learn. Res.419 citations
Semantic Scholar
Flexibly Fair Representation Learning by Disentanglement
Elliot Creager, David Madras, J. Jacobsen, Marissa A. Weis +3 more
2019International Conference on Machine Learning390 citations
Semantic Scholar
Freeze-Thaw Bayesian Optimization
Kevin Swersky, Jasper Snoek, Ryan P. Adams
2014arXiv.org303 citations
Semantic Scholar
Input Warping for Bayesian Optimization of Non-Stationary Functions
Jasper Snoek, Kevin Swersky, R. Zemel, Ryan P. Adams
2014International Conference on Machine Learning276 citations
Semantic Scholar
Video models are zero-shot learners and reasoners
Thaddäus Wiedemer, Yuxuan Li, Paul Vicol, Shi-Xiang Gu +5 more
2025arXiv.org234 citations
Semantic Scholar
Do generative video models understand physical principles?
Saman Motamed, Laura Culp, Kevin Swersky, P. Jaini +1 more
2025IEEE Workshop/Winter Conference on Applications of Computer Vision195 citations Open access
Semantic Scholar
Learning Sparse Networks Using Targeted Dropout
Aidan N. Gomez, Ivan Zhang, Siddhartha Rao Kamalakara, Divyam Madaan +3 more
2019arXiv.org105 citations
Semantic Scholar
Pre-trained Gaussian Processes for Bayesian Optimization
Z. Wang, G. Dahl, Kevin Swersky, Chansoo Lee +4 more
2021Journal of machine learning research100 citations
Semantic Scholar
Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces
Kevin Swersky, D. Duvenaud, Jasper Snoek, F. Hutter +1 more
201484 citations
Semantic Scholar
Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach
M. Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky +2 more
2020International Conference on Machine Learning76 citations
Semantic Scholar
Learning unbiased features
Yujia Li, Kevin Swersky, R. Zemel
2014arXiv.org74 citations
Semantic Scholar
Fast Exact Inference for Recursive Cardinality Models
Daniel Tarlow, Kevin Swersky, R. Zemel, Ryan P. Adams +1 more
2012Conference on Uncertainty in Artificial Intelligence62 citations
Semantic Scholar
Cardinality Restricted Boltzmann Machines
Kevin Swersky, I. Sutskever, Daniel Tarlow, R. Zemel +2 more
2012Neural Information Processing Systems44 citations
Semantic Scholar
Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning
Daniel Tarlow, Kevin Swersky, Laurent Charlin, I. Sutskever +1 more
2013International Conference on Machine Learning35 citations
Semantic Scholar
Improving Bayesian Optimization for Machine Learning using Expert Priors
Kevin Swersky
201721 citations
Semantic Scholar
Exploring and Benchmarking the Planning Capabilities of Large Language Models
Bernd Bohnet, Azade Nova, Aaron T. Parisi, Kevin Swersky +5 more
2024arXiv.org20 citations
Semantic Scholar
Probabilistic n-Choose-k Models for Classification and Ranking
Kevin Swersky, Brendan J. Frey, Daniel Tarlow, R. Zemel +1 more
2012Neural Information Processing Systems15 citations
Semantic Scholar
Long-Span Question-Answering: Automatic Question Generation and QA-System Ranking via Side-by-Side Evaluation
Bernd Bohnet, Kevin Swersky, Rosanne Liu, Pranjal Awasthi +8 more
2024arXiv.org13 citations
Semantic Scholar
Neural Networks for Modeling Source Code Edits
Rui Zhao, David Bieber, Kevin Swersky, Daniel Tarlow
2018arXiv.org12 citations
Semantic Scholar
Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single
Paul Vicol, Zico Kolter, Kevin Swersky
2023International Conference on Machine Learning10 citations Open access
Semantic Scholar
Pre-training helps Bayesian optimization too
Z. Wang, G. Dahl, Kevin Swersky, Chansoo Lee +5 more
2022arXiv.org10 citations Open access
Semantic Scholar
Efficient Feature Learning Using Perturb-and-MAP
Ke Li, Kevin Swersky, R. Zemel
201310 citations
Semantic Scholar
Enhancing LLM Planning Capabilities through Intrinsic Self-Critique
Bernd Bohnet, P. Kamienny, Hanie Sedghi, Dilan Görür +6 more
2025arXiv.org8 citations
Semantic Scholar
A Comparative Analysis of LLM Adaptation: SFT, LoRA, and ICL in Data-Scarce Scenarios
Bernd Bohnet, Rumen Dangovski, Kevin Swersky, Sherry Moore +3 more
2025arXiv.org8 citations
Semantic Scholar
SentenceMIM: A Latent Variable Language Model
M. Livne, Kevin Swersky, David J. Fleet
2020arXiv.org8 citations
Semantic Scholar
MIM: Mutual Information Machine
M. Livne, Kevin Swersky, David J. Fleet
2019arXiv.org8 citations
Semantic Scholar
Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability
Jiri Hron, Laura Culp, G. Elsayed, Rosanne Liu +27 more
2024arXiv.org6 citations
Semantic Scholar
Greedy Growing Enables High-Resolution Pixel-Based Diffusion Models
C. Vasconcelos, Abdullah Rashwan, Austin Waters, Trevor Walker +21 more
2024Trans. Mach. Learn. Res.4 citations
Semantic Scholar
Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5?
C. D. Freeman, Laura Culp, Aaron T. Parisi, Maxwell Bileschi +26 more
2023arXiv.org3 citations
Semantic Scholar
Automatic prior selection for meta Bayesian optimization with a case study on tuning deep neural network optimizers
Z. Wang, G. Dahl, Kevin Swersky, Chansoo Lee +5 more
2021arXiv.org3 citations
Semantic Scholar
Visual prompt engineering for video models
Robert Geirhos, Yuxuan Li, Thaddäus Wiedemer, N. Kalibhat +6 more
2026arXiv.org1 citations
Semantic Scholar
Few-shot Learning with Big Prototypes
Kelsey Allen, Evan Shelhamer, Hanul Shin, Mina Ghadimi Atigh +52 more
20221 citations
Semantic Scholar
Proceedings of the Second Workshop on Advances in Language and Vision Research
Er-Guo Wang, Santa Cruz, Rong-Hang Hu, Drew A. Hudson +408 more
20211 citations Open access
Semantic Scholar
Optimizing Long-term Social Welfare in Recommender Systems
M. Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky +2 more
20201 citations
Semantic Scholar
High Mutual Information in Representation Learning with Symmetric Variational Inference
M. Livne, Kevin Swersky, David J. Fleet
2019arXiv.org1 citations
Semantic Scholar
Mitigating Prototype Shift: Few-Shot Nested Named Entity Recognition with Prototype-Attention
Xu Han, Peng Xie, Haitao Zheng, C. Finn +22 more
20230 citations
Semantic Scholar
Bad priors, their threats to Bayesian optimization and some remedies via prior learning
Z. Wang, G. Dahl, Kevin Swersky, Chansoo Lee +5 more
20220 citations
Semantic Scholar
EW-SHOT L EARNING
Jake Snell, Kevin Swersky, R. Zemel
20160 citations
Semantic Scholar
UvA-DARE ( Digital Academic Repository ) The Variational Fair
Kevin Swersky, Yujia Li, M. Welling
0 citations
Semantic Scholar
H2R: A Human-to-Robot Data Augmentation for Robot Pre-training from Videos
Figure 1. H2R, Rohan Anil, Andrew M. Dai, Orhan Firat +496 more
0 citations
Semantic Scholar

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