Ari Pakman - RankMe

23 papers A* 5A 3Misc 1Journal 11Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Bayesian Circular Regression with von Mises Quasi-Processes. AISTATS Yarden Cohen, Alexandre K. W. Navarro, Jes Frellsen, Richard E. Turner, Raziel Riemer, Ari Pakman
2025	A*	`conf`	Clustering via Self-Supervised Diffusion. ICML Roy Uziel, Irit Chelly, Oren Freifeld, Ari Pakman
2025	J	`jnl`	Clustering via Self-Supervised Diffusion. CoRR Roy Uziel, Irit Chelly, Oren Freifeld, Ari Pakman
2025	A	`conf`	Consistent Amortized Clustering via Generative Flow Networks. AISTATS Irit Chelly, Roy Uziel, Oren Freifeld, Ari Pakman
2025	J	`jnl`	Consistent Amortized Clustering via Generative Flow Networks. CoRR Irit Chelly, Roy Uziel, Oren Freifeld, Ari Pakman
2025	J	`jnl`	Super-efficient exact Hamiltonian Monte Carlo for the von Mises distribution. Appl. Math. Lett. Ari Pakman
2024	J	`jnl`	von Mises Quasi-Processes for Bayesian Circular Regression. CoRR Yarden Cohen, Alexandre K. W. Navarro, Jes Frellsen, Richard E. Turner, Raziel Riemer, Ari Pakman
2021	A*	`conf`	Estimating the Unique Information of Continuous Variables. NeurIPS Ari Pakman, Amin Nejatbakhsh, Dar Gilboa, Abdullah Makkeh, Luca Mazzucato, Michael Wibral, Elad Schneidman
2021	J	`jnl`	Estimating the Unique Information of Continuous Variables. CoRR Ari Pakman, Dar Gilboa, Elad Schneidman
2021	J	`jnl`	Marginalizable Density Models. CoRR Dar Gilboa, Ari Pakman, Thibault Vatter
2020	J	`jnl`	Attentive Clustering Processes. CoRR Ari Pakman, Yueqi Wang, Yoonho Lee, Pallab Basu, Juho Lee, Yee Whye Teh, Liam Paninski
2020	A*	`conf`	Neural Clustering Processes. ICML Ari Pakman, Yueqi Wang, Catalin Mitelut, Jin Hyung Lee, Liam Paninski
2019	J	`jnl`	Discrete Neural Processes. CoRR Ari Pakman, Liam Paninski
2019	—	`conf`	Neural Permutation Processes. AABI Ari Pakman, Yueqi Wang, Liam Paninski
2018	J	`jnl`	Amortized Bayesian inference for clustering models. CoRR Ari Pakman, Liam Paninski
2017	A*	`conf`	Stochastic Bouncy Particle Sampler. ICML Ari Pakman, Dar Gilboa, David E. Carlson, Liam Paninski
2016	A*	`conf`	Partition Functions from Rao-Blackwellized Tempered Sampling. ICML David E. Carlson, Patrick Stinson, Ari Pakman, Liam Paninski
2016	A	`conf`	Taming the Noise in Reinforcement Learning via Soft Updates. UAI Roy Fox, Ari Pakman, Naftali Tishby
2015	J	`jnl`	G-Learning: Taming the Noise in Reinforcement Learning via Soft Updates. CoRR Roy Fox, Ari Pakman, Naftali Tishby
2014	J	`jnl`	Fast state-space methods for inferring dendritic synaptic connectivity. J. Comput. Neurosci. Ari Pakman, Jonathan Hunter Huggins, Carl Smith, Liam Paninski
2013	—	`conf`	Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions. NIPS Ari Pakman, Liam Paninski
2013	—	`conf`	Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits. NIPS Benjamin Shababo, Brooks Paige, Ari Pakman, Liam Paninski
2013	Misc	`conf`	Bayesian spike inference from calcium imaging data. ACSSC Eftychios A. Pnevmatikakis, Josh Merel, Ari Pakman, Liam Paninski