Sotabase

Career

· Faculty Member, UC Berkeley Berkeley Artificial Intelligence Research Lab (BAIR)2024–
· Professor Emeritus, Professor in the Graduate School, University of California, Berkeley2024–
· Professor and Director, AMPLab, University of California, Berkeley2013–2016
· Pehong Chen Distinguished Professor, University of California, Berkeley1998–
· Professor Emeritus, Pehong Chen Distinguished Professor, University of California, Berkeley1998–
· Professor of Statistics and Electrical Engineering and Computer Science, University of California, Berkeley1998–
· Professor, Massachusetts Institute of Technology (MIT)1988–1998
· PhD in Cognitive Science, University of California, San Diego1985–
· Master of Science in Mathematics, Arizona State University1980–
· Bachelor of Science in Psychology, Louisiana State University1978–
· Not explicitly specified, Berkeley Laboratory of Information and System Sciences (BLISS)

Publications (641)

Latent Dirichlet Allocation
2009
38,855
cited
AUTO-ENCODING VARIATIONAL BAYES
2020
21,128
cited
On Spectral Clustering: Analysis and an algorithm
Neural Information Processing Systems · 2001
10,552
cited
Trust Region Policy Optimization
International Conference on Machine Learning · 2015
7,583
cited
Adaptive Mixtures of Local Experts
Neural Computation · 1991
6,149
cited
Graphical Models, Exponential Families, and Variational Inference
Found. Trends Mach. Learn. · 2008
4,676
cited
An Introduction to Variational Methods for Graphical Models
Machine-mediated learning · 1999
4,593
cited
High-Dimensional Continuous Control Using Generalized Advantage Estimation
International Conference on Learning Representations · 2015
4,104
cited
Hierarchical Dirichlet Processes
2006
3,983
cited
An internal model for sensorimotor integration.
Science · 1995
3,465
cited
Distance Metric Learning with Application to Clustering with Side-Information
Neural Information Processing Systems · 2002
3,331
cited
Theoretically Principled Trade-off between Robustness and Accuracy
International Conference on Machine Learning · 2019
2,877
cited
Conditional Adversarial Domain Adaptation
Neural Information Processing Systems · 2017
2,658
cited
On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes
Neural Information Processing Systems · 2001
2,598
cited
Learning the Kernel Matrix with Semidefinite Programming
Journal of machine learning research · 2002
2,579
cited
Kalman filtering with intermittent observations
IEEE Transactions on Automatic Control · 2004
2,537
cited
Active Learning with Statistical Models
Neural Information Processing Systems · 1996
2,503
cited
Deep Generative Modeling for Single-cell Transcriptomics
Nature Methods · 2018
2,033
cited
Matching Words and Pictures
Journal of machine learning research · 2003
1,814
cited
Variational inference for Dirichlet process mixtures
2006
1,585
cited
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