See also my Google Scholar page.

2023
  • Spuriosity Didn’t Kill the Classifier: Harnessing Spurious Features with Invariant Predictions. arXiv
    With Cian Eastwood, Andrei Liviu Nicolicioiu, Marin Vlastelica, Julius von Kügelgen, and Bernhard Schölkopf.
    In Annual Conference on Neural Information Processing Systems (NeurIPS).
  • Staying and Returning Dynamics of Young Children's Attention. Online Data Code
    With Jaeah Kim, Catarina Vales, Emily Keebler, Anna Fisher, and Erik Thiessen.
    In Developmental Science.
  • Nonparametric Indirect Active Learning. arXiv
    In International Conference on Artificial Intelligence and Statistics (AISTATS).
    Short version presented at ICML 2022 Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML).
2022
  • Optimal Binary Classification Beyond Accuracy. arXiv Code
    Open math problem concerning the multiclass version of this result: PDF
    With Justin Khim.
    In Annual Conference on Neural Information Processing Systems (NeurIPS).
  • Probable Domain Generalization via Quantile Risk Minimization.
    arXiv Code
    With Cian Eastwood, Alexander Robey, Julius von Kügelgen, Hamed Hassani, George J. Pappas, and Bernhard Schölkopf.
    In Annual Conference on Neural Information Processing Systems (NeurIPS).
  • Decoding Attention from Gaze: A Benchmark Dataset and End-to-End Models.
    arXiv Code Data
    With Karan Uppal and Jaeah Kim.
    In Gaze Meets ML Workshop at NeurIPS 2022.
  • A Heirarchical Model of Attention over Time. PDF Code
    With Jaeah Kim, Dan Yurovsky, Anna Fisher, and Erik Thiessen.
    In Procecedings of the Annual Meeting of the Cognitive Science Society (CogSci).
2021
  • A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan. Online Preprint
    With Joseph Ledsam, Sercan Arik, Joel Shor, Rajarishi Sinha, Jinsung Yoon, Long Le, Michael Dusenberry, Nate Yoder, Kris Popendorf, Arkady Epshteyn, Johan Euphrosine, Elli Kanal, Isaac Jones, Chun-Liang Li, Beth Luan, Joe Mckenna, Vikas Menon, Mimi Sun, Ashwin Sura Ravi, Leyou Zhang, Dario Sava, Hiroki Kayama, Thomas Tsai, Daisuke Yoneoka, Shuhei Nomura, Hiroaki Miyata, and Tomas Pfister.
    In Nature Digital Medicine.
  • Continuum-Armed Bandits: A Function Space Perspective. arXiv Poster
    In International Conference on Artificial Intelligence and Statistics (AISTATS).
2020
  • Interpretable Covid-19 Forecasting. arXiv Fairness Analysis
    With Sercan O. Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T.Le, Vikas Menon, Leyou Zhang, Nate Yoder, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, and Tomas Pfister.
    In Annual Conference on Neural Information Processing Systems (NeurIPS).
  • Robust Density Estimation under Besov IPM losses. arXiv
    With Ananya Uppal and Barnabas Poczos.
    In Annual Conference on Neural Information Processing Systems (NeurIPS).
  • DARC: Differentiable ARchitecture Compression. arXiv
    With Ashish Khetan and Zohar Karnin.
    In ICLR Workshop on Neural Architecture Search.
  • Staying and Returning Dynamics of Sustained Attention in Young Children.
    PDF Code Data
    With Jaeah Kim, Erik D. Thiessen, and Anna V. Fisher.
    In Procecedings of the Annual Meeting of the Cognitive Science Society (CogSci).
2019
  • A Hidden Markov Model for Analyzing Eye-Tracking of Moving Objects.
    Online PsyArXiv Poster Code/Data
    With Jaeah Kim, Erik D. Thiessen, and Anna V. Fisher.
    In Behavior Research Methods.
    • Short version presented at the 2018 Annual Meeting of the Cognitive Science Society (CogSci). PDF Code/Data
  • Nonparametric Density Estimation & Convergence of GANs under Besov IPM Losses. arXiv Poster Talk Slides
    With Ananya Uppal and Barnabas Poczos.
    In Neural Information Processing Systems (NeurIPS).
    Honorable Mention for Outstanding Paper Award
  • Adjustment in tumbling rates improves bacterial chemotaxis on obstacle-laden terrains. Online Postprint           Press: Nature Reviews Microbiology Science Bulletin
    With Sabrina Rashid, Zhicheng Long, Maryam Kohram, Harsh Vashistha, Saket Navlakha, Hanna Salman, Zoltan N. Oltvai, and Ziv Bar-Joseph.
    In Proceedings of the National Academy of Sciences (PNAS).
  • A Bacterial based Distributed Gradient Descent Model for Mass Scale Evacuations. Paper Supporting Website, Code, and Movies
    With Sabrina Rashid, Saket Navlakha, and Ziv Bar-Joseph.
    In Swarm and Evolutionary Computation.
2018
  • Nonparametric Density Estimation with Adversarial Losses. arXiv Poster
    With Ananya Uppal, Boyue Li, Chun-Liang Li, Manzil Zaheer, and Barnabas Poczos.
    In Annual Conference on Neural Information Processing Systems (NeurIPS).
  • Predicting Enhancer-Promoter Interaction from Genomic Sequence with Deep Learning. Online bioRxiv
    With Yang Yang, Barnabas Poczos, and Jian Ma.
    In Quantitative Biology.
    • Early versions of this work were presented at the 2016 NIPS Workshop on Machine Learning in Computational Biology (MLCB) (Extended Abstract) and the 2017 Cold Spring Harbor Meeting on Systems Biology (Poster)
  • Minimax Reconstruction Risk of Convolutional Sparse Dictionary Learning.
    arXiv Code Poster
    With Barnabas Poczos and Jian Ma.
    International Conference on Artificial Intelligence and Statistics (AISTATS).
    • Short version presented at the 2017 Allerton Conference PDF Slides
2017
  • Nonparanormal Information Estimation. Paper Code Slides Poster
    With Barnabas Poczos.
    International Conference on Machine Learning (ICML).
  • Exploiting sequence-based features for predicting enhancer-promoter interactions. PDF Supplement
    With Yang Yang, Ruochi Zhang, and Jian Ma.
    Conference on Intelligent Systems for Molecular Biology (ISMB).
2016
  • Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators. Paper Poster
    With Barnabas Poczos.
    Annual Conference on Neural Information Processing Systems (NIPS).
  • Efficient Nonparametric Smoothness Estimation. Paper Poster Code
    With Simon Du and Barnabas Poczos.
    Annual Conference on Neural Information Processing Systems (NIPS)
  • Distributed Gradient Descent in Bacterial Food Search. arXiv Website Code
    With Sabrina Rashid, Saket Navlakha, and Ziv Bar-Joseph.
    International Conference on Research in Computational Molecular Biology (RECOMB), 2016.
    • An early version of this work was presented at the Workshop on Biological Distributed Algorithms (BDA), 2014 Extended Abstract Slides
2014
  • Exponential Concentration of a Density Functional Estimator. arXiv Poster
    With Barnabas Poczos.
    Annual Conference on Neural Information Processing Systems (NIPS).
  • Generalized Exponential Concentration Inequality for Renyi Divergence Estimation. arXiv Slides Poster
    With Barnabas Poczos.
    International Conference on Machine Learning (ICML).
Other Manuscripts The following manuscripts contain results that are (in my opinion) interesting or useful but not high priority to get formally published.
  • Multiclass Classification via Class-Weighted Nearest Neighbors. arXiv Code
    With Justin Khim and Neil Xu.
  • Minimax Distribution Estimation in Wasserstein Distance. arXiv
    With Barnabas Poczos.
  • Minimax Estimation of Quadratic Fourier Functionals. arXiv
    With Bharath Sriperumbudur and Barnabas Poczos.
  • Analysis of k-Nearest Neighbor Distances with Application to Entropy Estimation. PDF
    With Barnabas Poczos.
    This report studies convergence rates of the classic k-nearest neighbor entropy estimator of Kozachenko and Leonenko (1987). The results have been generalized to other functionals and published in the 2016 NIPS paper Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators (above).
Theses
  • Estimating Probability Distributions and their Properties. PhD Thesis. 2019. PDF
  • Estimating Probability Distributions and their Properties. PhD Proposal. 2018. PDF
  • Concentration Inequalities for Density Functionals. Undergraduate Honors Thesis. 2014. PDF