Alireza Makhzani

40 papers A* 12B 1Journal 21Unranked 6

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	A Computational Framework for Solving Wasserstein Lagrangian Flows. ICML Kirill Neklyudov, Rob Brekelmans, Alexander Tong, Lazar Atanackovic, Qiang Liu, Alireza Makhzani
2024	A*	`conf`	Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective. ICML Wu Lin, Felix Dangel, Runa Eschenhagen, Juhan Bae, Richard E. Turner, Alireza Makhzani
2024	J	`jnl`	Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective. CoRR Wu Lin, Felix Dangel, Runa Eschenhagen, Juhan Bae, Richard E. Turner, Alireza Makhzani
2024	A*	`conf`	Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo. ICML Stephen Zhao, Rob Brekelmans, Alireza Makhzani, Roger Baker Grosse
2024	J	`jnl`	Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo. CoRR Stephen Zhao, Rob Brekelmans, Alireza Makhzani, Roger B. Grosse
2024	A*	`conf`	Random Cycle Coding: Lossless Compression of Cluster Assignments via Bits-Back Coding. NeurIPS Daniel Severo, Ashish Khisti, Alireza Makhzani
2024	J	`jnl`	Random Cycle Coding: Lossless Compression of Cluster Assignments via Bits-Back Coding. CoRR Daniel Severo, Ashish Khisti, Alireza Makhzani
2024	A*	`conf`	Structured Inverse-Free Natural Gradient Descent: Memory-Efficient & Numerically-Stable KFAC. ICML Wu Lin, Felix Dangel, Runa Eschenhagen, Kirill Neklyudov, Agustinus Kristiadi, Richard E. Turner, Alireza Makhzani
2023	J	`jnl`	A Computational Framework for Solving Wasserstein Lagrangian Flows. CoRR Kirill Neklyudov, Rob Brekelmans, Alexander Tong, Lazar Atanackovic, Qiang Liu, Alireza Makhzani
2023	A*	`conf`	Action Matching: Learning Stochastic Dynamics from Samples. ICML Kirill Neklyudov, Rob Brekelmans, Daniel Severo, Alireza Makhzani
2023	J	`jnl`	Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. CoRR Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger B. Grosse, Alireza Makhzani
2023	A*	`conf`	One-Shot Compression of Large Edge-Exchangeable Graphs using Bits-Back Coding. ICML Daniel Severo, James Townsend, Ashish J. Khisti, Alireza Makhzani
2023	J	`jnl`	Quantum HyperNetworks: Training Binary Neural Networks in Quantum Superposition. CoRR Juan Carrasquilla, Mohamed Hibat-Allah, Estelle M. Inack, Alireza Makhzani, Kirill Neklyudov, Graham W. Taylor, Giacomo Torlai
2023	J	`jnl`	Random Edge Coding: One-Shot Bits-Back Coding of Large Labeled Graphs. CoRR Daniel Severo, James Townsend, Ashish Khisti, Alireza Makhzani
2023	J	`jnl`	Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC for Large Neural Nets. CoRR Wu Lin, Felix Dangel, Runa Eschenhagen, Kirill Neklyudov, Agustinus Kristiadi, Richard E. Turner, Alireza Makhzani
2023	A*	`conf`	Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation. NeurIPS Kirill Neklyudov, Jannes Nys, Luca A. Thiede, Juan Carrasquilla, Qiang Liu, Max Welling, Alireza Makhzani
2023	J	`jnl`	Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation. CoRR Kirill Neklyudov, Jannes Nys, Luca A. Thiede, Juan Carrasquilla, Qiang Liu, Max Welling, Alireza Makhzani
2022	J	`jnl`	Action Matching: A Variational Method for Learning Stochastic Dynamics from Samples. CoRR Kirill Neklyudov, Daniel Severo, Alireza Makhzani
2022	J	`jnl`	Compressing Multisets With Large Alphabets. IEEE J. Sel. Areas Inf. Theory Daniel Severo, James Townsend, Ashish Khisti, Alireza Makhzani, Karen Ullrich
2022	B	`conf`	Compressing Multisets with Large Alphabets. DCC Daniel Severo, James Townsend, Ashish Khisti, Alireza Makhzani, Karen Ullrich
2022	A*	`conf`	Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. ICLR Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger Baker Grosse, Alireza Makhzani
2022	J	`jnl`	Variational Model Inversion Attacks. CoRR Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard S. Zemel, Alireza Makhzani
2021	J	`jnl`	Compressing Multisets with Large Alphabets. CoRR Daniel Severo, James Townsend, Ashish Khisti, Alireza Makhzani, Karen Ullrich
2021	A*	`conf`	Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding. ICML Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison
2021	J	`jnl`	Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding. CoRR Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison
2021	A*	`conf`	Variational Model Inversion Attacks. NeurIPS Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard S. Zemel, Alireza Makhzani
2020	A*	`conf`	Evaluating Lossy Compression Rates of Deep Generative Models. ICML Sicong Huang, Alireza Makhzani, Yanshuai Cao, Roger B. Grosse
2020	J	`jnl`	Evaluating Lossy Compression Rates of Deep Generative Models. CoRR Sicong Huang, Alireza Makhzani, Yanshuai Cao, Roger B. Grosse
2020	J	`jnl`	Likelihood Ratio Exponential Families. CoRR Rob Brekelmans, Frank Nielsen, Alireza Makhzani, Aram Galstyan, Greg Ver Steeg
2018	J	`jnl`	Implicit Autoencoders. CoRR Alireza Makhzani
2017	—	`conf`	PixelGAN Autoencoders. NIPS Alireza Makhzani, Brendan J. Frey
2017	J	`jnl`	PixelGAN Autoencoders. CoRR Alireza Makhzani, Brendan J. Frey
2017	J	`jnl`	StarCraft II: A New Challenge for Reinforcement Learning. CoRR Oriol Vinyals, Timo Ewalds, Sergey Bartunov, Petko Georgiev, Alexander Sasha Vezhnevets, Michelle Yeo, Alireza Makhzani, Heinrich Küttler, John P. Agapiou, Julian Schrittwieser, John Quan, Stephen Gaffney, Stig Petersen, Karen Simonyan, Tom Schaul, Hado van Hasselt, David Silver, Timothy P. Lillicrap, Kevin Calderone, Paul Keet, Anthony Brunasso, David Lawrence, Anders Ekermo, Jacob Repp, Rodney Tsing
2015	J	`jnl`	Adversarial Autoencoders. CoRR Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian J. Goodfellow
2015	—	`conf`	Winner-Take-All Autoencoders. NIPS Alireza Makhzani, Brendan J. Frey
2014	J	`jnl`	A Winner-Take-All Method for Training Sparse Convolutional Autoencoders. CoRR Alireza Makhzani, Brendan J. Frey
2014	—	`conf`	k-Sparse Autoencoders. ICLR (Poster) Alireza Makhzani, Brendan J. Frey
2013	—	`conf`	Distributed spectrum sensing in cognitive radios via graphical models. CAMSAP Alireza Makhzani, Shahrokh Valaee
2012	—	`conf`	Reconstruction of jointly sparse signals using iterative hard thresholding. ICC Alireza Makhzani, Shahrokh Valaee
2011	—	`conf`	Reconstruction of a Generalized Joint Sparsity Model using Principal Component Analysis. CAMSAP Alireza Makhzani, Shahrokh Valaee