Alireza Makhzani

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 27

Top Topics

Compression Rate

Generative Model

Top Venues

Publications

Wu Lin, Felix Dangel, Runa Eschenhagen, Juhan Bae, Richard E. Turner, Alireza Makhzani
Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective. CoRR (2024)
Stephen Zhao, Rob Brekelmans, Alireza Makhzani, Roger B. Grosse
Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo. CoRR (2024)
Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger B. Grosse, Alireza Makhzani
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. CoRR (2023)
Wu Lin, Felix Dangel, Runa Eschenhagen, Kirill Neklyudov, Agustinus Kristiadi, Richard E. Turner, Alireza Makhzani
Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC for Large Neural Nets. CoRR (2023)
Kirill Neklyudov, Jannes Nys, Luca Thiede, Juan Carrasquilla, Qiang Liu, Max Welling, Alireza Makhzani
Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation. CoRR (2023)
Kirill Neklyudov, Rob Brekelmans, Daniel Severo, Alireza Makhzani
Action Matching: Learning Stochastic Dynamics from Samples. ICML (2023)
Daniel Severo, James Townsend, Ashish J. Khisti, Alireza Makhzani
One-Shot Compression of Large Edge-Exchangeable Graphs using Bits-Back Coding. ICML (2023)
Juan Carrasquilla, Mohamed Hibat-Allah, Estelle M. Inack, Alireza Makhzani, Kirill Neklyudov, Graham W. Taylor, Giacomo Torlai
Quantum HyperNetworks: Training Binary Neural Networks in Quantum Superposition. CoRR (2023)
Daniel Severo, James Townsend, Ashish Khisti, Alireza Makhzani
Random Edge Coding: One-Shot Bits-Back Coding of Large Labeled Graphs. CoRR (2023)
Kirill Neklyudov, Jannes Nys, Luca Thiede, Juan Carrasquilla, Qiang Liu, Max Welling, Alireza Makhzani
Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation. NeurIPS (2023)
Kirill Neklyudov, Rob Brekelmans, Alexander Tong, Lazar Atanackovic, Qiang Liu, Alireza Makhzani
A Computational Framework for Solving Wasserstein Lagrangian Flows. CoRR (2023)
Daniel Severo, James Townsend, Ashish Khisti, Alireza Makhzani, Karen Ullrich
Compressing Multisets with Large Alphabets. DCC (2022)
Kirill Neklyudov, Daniel Severo, Alireza Makhzani
Action Matching: A Variational Method for Learning Stochastic Dynamics from Samples. CoRR (2022)
Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard S. Zemel, Alireza Makhzani
Variational Model Inversion Attacks. CoRR (2022)
Daniel Severo, James Townsend, Ashish Khisti, Alireza Makhzani, Karen Ullrich
Compressing Multisets With Large Alphabets. IEEE J. Sel. Areas Inf. Theory 3 (4) (2022)
Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger Baker Grosse, Alireza Makhzani
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. ICLR (2022)
Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding. ICML (2021)
Daniel Severo, James Townsend, Ashish Khisti, Alireza Makhzani, Karen Ullrich
Compressing Multisets with Large Alphabets. CoRR (2021)
Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard S. Zemel, Alireza Makhzani
Variational Model Inversion Attacks. NeurIPS (2021)
Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding. CoRR (2021)
Rob Brekelmans, Frank Nielsen, Alireza Makhzani, Aram Galstyan, Greg Ver Steeg
Likelihood Ratio Exponential Families. CoRR (2020)
Sicong Huang, Alireza Makhzani, Yanshuai Cao, Roger B. Grosse
Evaluating Lossy Compression Rates of Deep Generative Models. ICML (2020)
Sicong Huang, Alireza Makhzani, Yanshuai Cao, Roger B. Grosse
Evaluating Lossy Compression Rates of Deep Generative Models. CoRR (2020)
Alireza Makhzani
Implicit Autoencoders. CoRR (2018)
Alireza Makhzani, Brendan J. Frey
PixelGAN Autoencoders. NIPS (2017)
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
StarCraft II: A New Challenge for Reinforcement Learning. CoRR (2017)
Alireza Makhzani, Brendan J. Frey
PixelGAN Autoencoders. CoRR (2017)
Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian J. Goodfellow
Adversarial Autoencoders. CoRR (2015)
Alireza Makhzani, Brendan J. Frey
Winner-Take-All Autoencoders. NIPS (2015)
Alireza Makhzani, Brendan J. Frey
A Winner-Take-All Method for Training Sparse Convolutional Autoencoders. CoRR (2014)
Alireza Makhzani, Brendan J. Frey
k-Sparse Autoencoders. ICLR (Poster) (2014)
Alireza Makhzani, Shahrokh Valaee
Distributed spectrum sensing in cognitive radios via graphical models. CAMSAP (2013)
Alireza Makhzani, Shahrokh Valaee
Reconstruction of jointly sparse signals using iterative hard thresholding. ICC (2012)
Alireza Makhzani, Shahrokh Valaee
Reconstruction of a Generalized Joint Sparsity Model using Principal Component Analysis. CAMSAP (2011)