Priyank Jaini

39 papers A* 12A 1B 1Journal 21Unranked 3
YearRankTypeTitle / Venue / Authors
2025 J jnl
Amortized In-Context Bayesian Posterior Estimation.
CoRR
Sarthak Mittal, Niels Bracher, Guillaume Lajoie, Priyank Jaini, Marcus A. Brubaker
2025 J jnl
Do generative video models learn physical principles from watching videos?
CoRR
Saman Motamed, Laura Culp, Kevin Swersky, Priyank Jaini, Robert Geirhos
2025 A* conf
Towards flexible perception with visual memory.
ICML
Robert Geirhos, Priyank Jaini, Austin Stone, Sourabh Medapati, Xi Yi, George Toderici, Abhijit Ogale, Jonathon Shlens
2025 J jnl
Video models are zero-shot learners and reasoners.
CoRR
Thaddäus Wiedemer, Yuxuan Li, Paul Vicol, Shixiang Shane Gu, Nick Matarese, Kevin Swersky, Been Kim, Priyank Jaini, Robert Geirhos
2024 A* conf
Decoupling Semantic Similarity from Spatial Alignment for Neural Networks.
NeurIPS
Tassilo Wald, Constantin Ulrich, Priyank Jaini, Gregor Köhler, David Zimmerer, Stefan Denner, Fabian Isensee, Michael Baumgartner, Klaus H. Maier-Hein
2024 J jnl
Decoupling Semantic Similarity from Spatial Alignment for Neural Networks.
CoRR
Tassilo Wald, Constantin Ulrich, Gregor Köhler, David Zimmerer, Stefan Denner, Michael Baumgartner, Fabian Isensee, Priyank Jaini, Klaus H. Maier-Hein
2024 A* conf
Intriguing Properties of Generative Classifiers.
ICLR
Priyank Jaini, Kevin Clark, Robert Geirhos
2024 J jnl
Towards flexible perception with visual memory.
CoRR
Robert Geirhos, Priyank Jaini, Austin Stone, Sourabh Medapati, Xi Yi, George Toderici, Abhijit Ogale, Jonathon Shlens
2023 J jnl
Intriguing properties of generative classifiers.
CoRR
Priyank Jaini, Kevin Clark, Robert Geirhos
2023 A* conf
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths.
NeurIPS
Lars Holdijk, Yuanqi Du, Ferry Hooft, Priyank Jaini, Bernd Ensing, Max Welling
2023 A* conf
Text-to-Image Diffusion Models are Zero Shot Classifiers.
NeurIPS
Kevin Clark, Priyank Jaini
2023 J jnl
Text-to-Image Diffusion Models are Zero-Shot Classifiers.
CoRR
Kevin Clark, Priyank Jaini
2022 J jnl
Path Integral Stochastic Optimal Control for Sampling Transition Paths.
CoRR
Lars Holdijk, Yuanqi Du, Ferry Hooft, Priyank Jaini, Bernd Ensing, Max Welling
2022 J jnl
Recent Advancements in Tractable Probabilistic Inference (Dagstuhl Seminar 22161).
Dagstuhl Reports
Priyank Jaini, Kristian Kersting, Antonio Vergari, Max Welling
2021 A* conf
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions.
NeurIPS
Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling
2021 J jnl
Argmax Flows and Multinomial Diffusion: Towards Non-Autoregressive Language Models.
CoRR
Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling
2021 A* conf
Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent.
NeurIPS
Priyank Jaini, Lars Holdijk, Max Welling
2021 J jnl
Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent.
CoRR
Priyank Jaini, Lars Holdijk, Max Welling
2021 J jnl
Particle Dynamics for Learning EBMs.
CoRR
Kirill Neklyudov, Priyank Jaini, Max Welling
2021 A conf
Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC.
AISTATS
Priyank Jaini, Didrik Nielsen, Max Welling
2021 J jnl
Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC.
CoRR
Priyank Jaini, Didrik Nielsen, Max Welling
2021 A* conf
Self Normalizing Flows.
ICML
T. Anderson Keller, Jorn W. T. Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling
2020 J jnl
Complete Hierarchy of Relaxation for Constrained Signomial Positivity.
CoRR
Allen Houze Wang, Priyank Jaini, Yaoliang Yu, Pascal Poupart
2020 J jnl
Learning directed acyclic graph SPNs in sub-quadratic time.
Int. J. Approx. Reason.
Amur Ghose, Priyank Jaini, Pascal Poupart
2020 J jnl
Self Normalizing Flows.
CoRR
T. Anderson Keller, Jorn W. T. Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling
2020 A* conf
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows.
NeurIPS
Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling
2020 J jnl
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows.
CoRR
Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling
2020 A* conf
Tails of Lipschitz Triangular Flows.
ICML
Priyank Jaini, Ivan Kobyzev, Yaoliang Yu, Marcus A. Brubaker
2019 — —
Likelihood-based Density Estimation using Deep Architectures.
Priyank Jaini
2019 A* conf
Sum-of-Squares Polynomial Flow.
ICML
Priyank Jaini, Kira A. Selby, Yaoliang Yu
2019 J jnl
Sum-of-Squares Polynomial Flow.
CoRR
Priyank Jaini, Kira A. Selby, Yaoliang Yu
2019 J jnl
Tails of Triangular Flows.
CoRR
Priyank Jaini, Ivan Kobyzev, Marcus A. Brubaker, Yaoliang Yu
2018 A* conf
Deep Homogeneous Mixture Models: Representation, Separation, and Approximation.
NeurIPS
Priyank Jaini, Pascal Poupart, Yaoliang Yu
2018 — conf
Prometheus : Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks.
PGM
Priyank Jaini, Amur Ghose, Pascal Poupart
2017 J jnl
Accuracy Maximization Analysis for Sensory-Perceptual Tasks: Computational Improvements, Filter Robustness, and Coding Advantages for Scaled Additive Noise.
PLoS Comput. Biol.
Johannes Burge, Priyank Jaini
2017 — conf
Online Bayesian Transfer Learning for Sequential Data Modeling.
ICLR (Poster)
Priyank Jaini, Zhitang Chen, Pablo Carbajal, Edith Law, Laura Middleton, Kayla Regan, Mike Schaekermann, George Trimponias, James Tung, Pascal Poupart
2016 — conf
Online Algorithms for Sum-Product Networks with Continuous Variables.
Probabilistic Graphical Models
Priyank Jaini, Abdullah Rashwan, Han Zhao, Yue Liu, Ershad Banijamali, Zhitang Chen, Pascal Poupart
2016 J jnl
Online and Distributed learning of Gaussian mixture models by Bayesian Moment Matching.
CoRR
Priyank Jaini, Pascal Poupart
2016 B conf
Online flow size prediction for improved network routing.
ICNP
Pascal Poupart, Zhitang Chen, Priyank Jaini, Fred Fung, Hengky Susanto, Yanhui Geng, Li Chen, Kai Chen, Hao Jin