José Miguel Hernández-Lobato

José Miguel Hernández-Lobato

Professor of Machine Learning, University of Cambridge
Verified email at cam.ac.uk
Cited by 15258
Bayesian deep learning approximate inference deep generative modeling automatic molecular design reinforcement learning
Hanjun Dai

Hanjun Dai

Google DeepMind
Verified email at google.com
Cited by 9590
Deep Generative Modeling Sampling Discrete Optimization
Michael D Ward

Michael D Ward

Machine Learning Scientist, Generate Biomedicines
Verified email at generatebiomedicines.com
Cited by 1027
Deep Generative Modeling Protein Biophysics Few-shot learning
Sungmin Hong

Sungmin Hong

Applied Scientist II, AWS Generative AI Innovation Center
Verified email at amazon.com
Cited by 417
Machine Learning Generative AI Medical Image Analysis Deep Generative Modeling Nonlinear
Hao Wu

Hao Wu

Northeastern University
Verified email at northeastern.edu
Cited by 242
Deep Generative Modeling Variational Inference Representation Learning
Khalid Saifullah

Khalid Saifullah

PhD Student of Computer Science, University of Maryland
Verified email at cs.umd.edu
Cited by 172
Deep Learning Deep Generative Modeling Multimodal Representation Learning
Muhammad Izzatullah

Muhammad Izzatullah

PhD
Verified email at kaust.edu.sa
Cited by 131
Uncertainty Quantification Deep Learning Deep Generative Modeling Inverse Problems
Koichi Saito

Koichi Saito

SonyAI
Verified email at sony.com
Cited by 73
Deep generative modeling Music Technology Audio signal processing Machine learning
Niksa Praljak

Niksa Praljak

PhD Candidate in Biophysics at University of Chicago
Verified email at uchicago.edu
Cited by 38
protein design deep generative modeling biophysics synthetic biology
Ericsson Tetteh Chenebuah

Ericsson Tetteh Chenebuah

Department of Mechanical Engineering, University of Ottawa
Verified email at uottawa.ca
Cited by 26
artificial intelligence machine learning deep generative modeling energy optimization solid-state materials
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