Shakir Mohamed
19 papers · 2008–2023 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+9 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (44) π Academic Marathon Β· Full π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
π§
Keyword Pioneer
π
Keyword Champion
π
Triple Crown
π
Trend Setter
π
Conference Pioneer
π₯
Unstoppable Β· Bronze
π
Century Club Β· Bronze
π
Renaissance Researcher
(5)
ποΈ
Keyword Collector
(124)
Top co-authors
Research topics
Machine Learning
(17)
Deep Learning
(13)
Optimization & Theory
(13)
Models
(11)
Artificial Intelligence
(10)
Bayesian & Probabilistic Β· Artificial Intelligence
(8)
Bayesian & Probabilistic Β· Machine Learning
(8)
Core Methods
(5)
Learning Types Β· Machine Learning
(5)
Learning Types Β· Deep Learning
(4)
Core AI
(3)
Computer Vision
(1)
Data Science & Analytics
(1)
Mathematics & Optimization
(1)
Reinforcement Learning
(1)
Keywords
variational inference
(8)
bayesian inference
(4)
approximate inference
(4)
deep generative model
(4)
generative adversarial network
(3)
message passing
(2)
markov chain monte carlo
(2)
probabilistic model
(2)
gaussian process
(2)
normalizing flow
(2)
gaussian processes
(2)
reinforcement learning
(1)
ordinal regression
(1)
game theory
(1)
divergence minimization
(1)
3d reconstruction
(1)
stochastic optimization
(1)
probabilistic modeling
(1)
probabilistic inference
(1)
dimensionality reduction
(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
NeurIPS 2019
Implicit Reparameterization Gradients
NeurIPS 2018
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
Unsupervised Learning of 3D Structure from Images
NeurIPS 2016
Variational Inference with Normalizing Flows
ICML 2015
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning
NeurIPS 2015
Semi-supervised Learning with Deep Generative Models
NeurIPS 2014
Stochastic Backpropagation and Approximate Inference in Deep Generative Models
ICML 2014
Adaptive Hamiltonian and Riemann Manifold Monte Carlo
ICML 2013
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models
AISTATS 2012
Expectation Propagation in Gaussian Process Dynamical Systems
NeurIPS 2012
Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression
NeurIPS 2012
On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models
AISTATS 2012
Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process
NeurIPS 2009
Bayesian Exponential Family PCA
NeurIPS 2008