Jaini, Priyank

19 publications

ICML 2025 Towards Flexible Perception with Visual Memory Robert Geirhos, Priyank Jaini, Austin Stone, Sourabh Medapati, Xi Yi, George Toderici, Abhijit Ogale, Jonathon Shlens

ICLR 2024 Intriguing Properties of Generative Classifiers Priyank Jaini, Kevin Clark, Robert Geirhos

ICMLW 2023 Exploring Exchangeable Dataset Amortization for Bayesian Posterior Inference Sarthak Mittal, Niels Leif Bracher, Guillaume Lajoie, Priyank Jaini, Marcus A Brubaker

NeurIPS 2023 Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths Lars Holdijk, Yuanqi Du, Ferry Hooft, Priyank Jaini, Berend Ensing, Max Welling

NeurIPS 2023 Text-to-Image Diffusion Models Are Zero Shot Classifiers Kevin Clark, Priyank Jaini

ICLRW 2023 Text-to-Image Diffusion Models Are Zero-Shot Classifiers Kevin Clark, Priyank Jaini

ICMLW 2022 Path Integral Stochastic Optimal Control for Sampling Transition Paths Lars Holdijk, Yuanqi Du, Priyank Jaini, Ferry Hooft, Bernd Ensing, Max Welling

AISTATS 2021 Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC Priyank Jaini, Didrik Nielsen, Max Welling

NeurIPS 2021 Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling

NeurIPS 2021 Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent Priyank Jaini, Lars Holdijk, Max Welling

NeurIPSW 2021 Particle Dynamics for Learning EBMs Kirill Neklyudov, Priyank Jaini, Max Welling

ICML 2021 Self Normalizing Flows Thomas A Keller, Jorn W.T. Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling

NeurIPS 2020 SurVAE Flows: Surjections to Bridge the Gap Between VAEs and Flows Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling

ICML 2020 Tails of Lipschitz Triangular Flows Priyank Jaini, Ivan Kobyzev, Yaoliang Yu, Marcus Brubaker

ICML 2019 Sum-of-Squares Polynomial Flow Priyank Jaini, Kira A. Selby, Yaoliang Yu

NeurIPS 2018 Deep Homogeneous Mixture Models: Representation, Separation, and Approximation Priyank Jaini, Pascal Poupart, Yaoliang Yu

PGM 2018 Prometheus : Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks Priyank Jaini, Amur Ghose, Pascal Poupart

ICLR 2017 Online Bayesian Transfer Learning for Sequential Data Modeling Priyank Jaini, Zhitang Chen, Pablo Carbajal, Edith Law, Laura Middleton, Kayla Regan, Mike Schaekermann, George Trimponias, James Tung, Pascal Poupart

PGM 2016 Online Algorithms for Sum-Product Networks with Continuous Variables Priyank Jaini, Abdullah Rashwan, Han Zhao, Yue Liu, Ershad Banijamali, Zhitang Chen, Pascal Poupart