Alexander A. Alemi

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 41

Top Topics

Mutual Information

Information Bottleneck

Confidence Measure

Imitation Learning

Top Venues

Publications

Mitchell Wortsman, Peter J. Liu, Lechao Xiao, Katie E. Everett, Alexander A. Alemi, Ben Adlam, John D. Co-Reyes, Izzeddin Gur, Abhishek Kumar, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein, Kelvin Xu, Jaehoon Lee, Justin Gilmer, Simon Kornblith
Small-scale proxies for large-scale Transformer training instabilities. ICLR (2024)
Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron T. Parisi, Abhishek Kumar, Alexander A. Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin Fathy Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. Trans. Mach. Learn. Res. 2024 (2024)
Katie Everett, Lechao Xiao, Mitchell Wortsman, Alexander A. Alemi, Roman Novak, Peter J. Liu, Izzeddin Gur, Jascha Sohl-Dickstein, Leslie Pack Kaelbling, Jaehoon Lee, Jeffrey Pennington
Scaling Exponents Across Parameterizations and Optimizers. CoRR (2024)
Alexander A. Alemi, Ben Poole
Variational Prediction. CoRR (2023)
Inbar Seroussi, Alexander A. Alemi, Moritz Helias, Zohar Ringel
Speed Limits for Deep Learning. CoRR (2023)
Yangjun Ruan, Saurabh Singh, Warren Richard Morningstar, Alexander A. Alemi, Sergey Ioffe, Ian Fischer, Joshua V. Dillon
Weighted Ensemble Self-Supervised Learning. ICLR (2023)
Yuqing Du, Daniel Ho, Alexander A. Alemi, Eric Jang, Mohi Khansari
Bayesian Imitation Learning for End-to-End Mobile Manipulation. CoRR (2022)
Yangjun Ruan, Saurabh Singh, Warren R. Morningstar, Alexander A. Alemi, Sergey Ioffe, Ian Fischer, Joshua V. Dillon
Weighted Ensemble Self-Supervised Learning. CoRR (2022)
Iryna Korshunova, David Stutz, Alexander A. Alemi, Olivia Wiles, Sven Gowal
A Closer Look at the Adversarial Robustness of Information Bottleneck Models. CoRR (2021)
Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A. Alemi, Andrew Gordon Wilson
Does Knowledge Distillation Really Work? CoRR (2021)
Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A. Alemi, Andrew Gordon Wilson
Does Knowledge Distillation Really Work? NeurIPS (2021)
Ian Fischer, Alexander A. Alemi
CEB Improves Model Robustness. CoRR (2020)
Roman Novak, Lechao Xiao, Jiri Hron, Jaehoon Lee, Alexander A. Alemi, Jascha Sohl-Dickstein, Samuel S. Schoenholz
Neural Tangents: Fast and Easy Infinite Neural Networks in Python. ICLR (2020)
Alexander A. Alemi, Warren R. Morningstar, Ben Poole, Ian Fischer, Joshua V. Dillon
VIB is Half Bayes. CoRR (2020)
Ian Fischer, Alexander A. Alemi
CEB Improves Model Robustness. Entropy 22 (10) (2020)
Warren R. Morningstar, Cusuh Ham, Andrew G. Gallagher, Balaji Lakshminarayanan, Alexander A. Alemi, Joshua V. Dillon
Density of States Estimation for Out-of-Distribution Detection. CoRR (2020)
Warren R. Morningstar, Alexander A. Alemi, Joshua V. Dillon
-Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime. CoRR (2020)
Zhe Dong, Deniz Oktay, Ben Poole, Alexander A. Alemi
On Predictive Information Sub-optimality of RNNs. CoRR (2019)
Alexander A. Alemi
Variational Predictive Information Bottleneck. AABI (2019)
Alexander A. Alemi
Variational Predictive Information Bottleneck. CoRR (2019)
Colin B. Clement, Matthew Bierbaum, Kevin P. O'Keeffe, Alexander A. Alemi
On the Use of ArXiv as a Dataset. CoRR (2019)
Ben Poole, Sherjil Ozair, Aäron van den Oord, Alexander A. Alemi, George Tucker
On Variational Bounds of Mutual Information. CoRR (2019)
Ravid Shwartz-Ziv, Alexander A. Alemi
Information in Infinite Ensembles of Infinitely-Wide Neural Networks. CoRR (2019)
Roman Novak, Lechao Xiao, Jiri Hron, Jaehoon Lee, Alexander A. Alemi, Jascha Sohl-Dickstein, Samuel S. Schoenholz
Neural Tangents: Fast and Easy Infinite Neural Networks in Python. CoRR (2019)
Ravid Shwartz-Ziv, Alexander A. Alemi
Information in Infinite Ensembles of Infinitely-Wide Neural Networks. AABI (2019)
Alexander A. Alemi, Ben Poole, Ian Fischer, Joshua V. Dillon, Rif A. Saurous, Kevin Murphy
Fixing a Broken ELBO. ICML (2018)
Emily Fertig, Aryan Arbabi, Alexander A. Alemi
β-VAEs can retain label information even at high compression. CoRR (2018)
Alexander A. Alemi, Ian Fischer, Joshua V. Dillon
Uncertainty in the Variational Information Bottleneck. CoRR (2018)
Alexander A. Alemi, Ian Fischer
GILBO: One Metric to Measure Them All. NeurIPS (2018)
Alexander A. Alemi, Ian Fischer
GILBO: One Metric to Measure Them All. ICLR (Workshop) (2018)
Sami Abu-El-Haija, Bryan Perozzi, Rami Al-Rfou, Alexander A. Alemi
Watch Your Step: Learning Node Embeddings via Graph Attention. NeurIPS (2018)
Alexander A. Alemi, Ian Fischer
GILBO: One Metric to Measure Them All. CoRR (2018)
Alexander A. Alemi, Ian Fischer
TherML: Thermodynamics of Machine Learning. CoRR (2018)
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alexander A. Alemi
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning. AAAI (2017)
Alexander A. Alemi, Ian Fischer, Joshua V. Dillon, Kevin Murphy
Deep Variational Information Bottleneck. ICLR (Poster) (2017)
Lorien X. Hayden, Alexander A. Alemi, Paul H. Ginsparg, James P. Sethna
Jeffrey's prior sampling of deep sigmoidal networks. CoRR (2017)
Alexander A. Alemi, Ben Poole, Ian Fischer, Joshua V. Dillon, Rif A. Saurous, Kevin Murphy
An Information-Theoretic Analysis of Deep Latent-Variable Models. CoRR (2017)
Alexander A. Alemi, Ian Fischer, Joshua V. Dillon, Kevin Murphy
Deep Variational Information Bottleneck. CoRR (2016)
Alexander A. Alemi, François Chollet, Geoffrey Irving, Christian Szegedy, Josef Urban
DeepMath - Deep Sequence Models for Premise Selection. CoRR (2016)
Geoffrey Irving, Christian Szegedy, Alexander A. Alemi, Niklas Eén, François Chollet, Josef Urban
DeepMath - Deep Sequence Models for Premise Selection. NIPS (2016)
Ben Poole, Alexander A. Alemi, Jascha Sohl-Dickstein, Anelia Angelova
Improved generator objectives for GANs. CoRR (2016)
Alexander A. Alemi, Paul Ginsparg
Text Segmentation based on Semantic Word Embeddings. CoRR (2015)
J. Massey Cashore, Xiaoting Zhao, Alexander A. Alemi, Yujia Liu, Peter I. Frazier
Clustering via Content-Augmented Stochastic Blockmodels. CoRR (2015)