Shakir Mohamed
19 papers · 2008–2023 · 6 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Renaissance Researcher (5) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (14) π£ Hot Topic Early Bird
πΊοΈ
Taxonomy Completionist
(14)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π
Triple Crown
π
Keyword Champion
π
Trend Setter
π₯
Unstoppable
(5)
π
Conference Pioneer
ποΈ
Keyword Collector
(111)
π
Century Club
(19)
Conferences
NIPS (9)
ICML (4)
AISTATS (2)
JMLR (2)
CVPR (1)
ICLR (1)
Top co-authors
Keywords
variational inference
(8)
deep generative model
(4)
approximate inference
(4)
bayesian inference
(4)
gaussian processes
(2)
normalizing flow
(2)
generative adversarial network
(2)
markov chain monte carlo
(2)
probabilistic model
(2)
gaussian process
(2)
semi-supervised learning
(1)
principal component analysis
(1)
matrix factorization
(1)
reinforcement learning
(1)
deep reinforcement learning
(1)
probabilistic modeling
(1)
3d reconstruction
(1)
3d vision
(1)
image synthesis
(1)
text generation
(1)
Papers
Understanding Deep Generative Models With Generalized Empirical Likelihoods
CVPR 2023
Normalizing Flows for Probabilistic Modeling and Inference
JMLR 2021
Monte Carlo Gradient Estimation in Machine Learning
JMLR 2020
Training Language GANs from Scratch
NIPS 2019
Learning Implicit Generative Models with the Method of Learned Moments
ICML 2018
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step
ICLR 2018
Implicit Reparameterization Gradients
NIPS 2018
Unsupervised Learning of 3D Structure from Images
NIPS 2016
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning
NIPS 2015
Variational Inference with Normalizing Flows
ICML 2015
Semi-supervised Learning with Deep Generative Models
NIPS 2014
Stochastic Backpropagation and Approximate Inference in Deep Generative Models
ICML 2014
Adaptive Hamiltonian and Riemann Manifold Monte Carlo
ICML 2013
On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models
AISTATS 2012
Expectation Propagation in Gaussian Process Dynamical Systems
NIPS 2012
Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression
NIPS 2012
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models
AISTATS 2012
Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process
NIPS 2009
Bayesian Exponential Family PCA
NIPS 2008