Shakir Mohamed

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 52

Top Venues

University of Cambridge, UK (PHD)

Education History

University of Cambridge, UK

PHD

Publications

Piotr Mirowski, David Warde-Farley, Mihaela Rosca, Matthew Koichi Grimes, Yana Hasson, Hyunjik Kim, Mélanie Rey, Simon Osindero, Suman V. Ravuri, Shakir Mohamed
Neural Compression of Atmospheric States. CoRR (2024)
Piotr W. Mirowski, Juliette Love, Kory W. Mathewson, Shakir Mohamed
A Robot Walks into a Bar: Can Language Models Serve as Creativity Support Tools for Comedy? An Evaluation of LLMs' Humour Alignment with Comedians. CoRR (2024)
William Agnew, A. Stevie Bergman, Jennifer Chien, Mark Díaz, Seliem El-Sayed, Jaylen Pittman, Shakir Mohamed, Kevin R. McKee
The Illusion of Artificial Inclusion. CHI (2024)
Irina Jurenka, Markus Kunesch, Kevin R. McKee, Daniel Gillick, Shaojian Zhu, Sara Wiltberger, Shubham Milind Phal, Katherine L. Hermann, Daniel Kasenberg, Avishkar Bhoopchand, Ankit Anand, Miruna Pîslar, Stephanie Chan, Lisa Wang, Jennifer She, Parsa Mahmoudieh, Aliya Rysbek, Wei-Jen Ko, Andrea Huber, Brett Wiltshire, Gal Elidan, Roni Rabin, Jasmin Rubinovitz, Amit Pitaru, Mac McAllister, Julia Wilkowski, David Choi, Roee Engelberg, Lidan Hackmon, Adva Levin, Rachel Griffin, Michael Sears, Filip Bar, Mia Mesar, Mana Jabbour, Arslan Chaudhry, James Cohan, Sridhar Thiagarajan, Nir Levine, Ben Brown, Dilan Görür, Svetlana Grant, Rachel Hashimshoni, Laura Weidinger, Jieru Hu, Dawn Chen, Kuba Dolecki, Canfer Akbulut, Maxwell L. Bileschi, Laura Culp, Wen-Xin Dong, Nahema Marchal, Kelsie Van Deman, Hema Bajaj Misra, Michael Duah, Moran Ambar, Avi Caciularu, Sandra Lefdal, Christopher Summerfield, James An, Pierre-Alexandre Kamienny, Abhinit Mohdi, Theofilos Strinopoulous, Annie Hale, Wayne Anderson, Luis C. Cobo, Niv Efron, Muktha Ananda, Shakir Mohamed, Maureen Heymans, Zoubin Ghahramani, Yossi Matias, Ben Gomes, Lila Ibrahim
Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach. CoRR (2024)
Piotr Mirowski, Juliette Love, Kory W. Mathewson, Shakir Mohamed
A Robot Walks into a Bar: Can Language Models Serve as Creativity SupportTools for Comedy? An Evaluation of LLMs' Humour Alignment with Comedians. FAccT (2024)
William Agnew, A. Stevie Bergman, Jennifer Chien, Mark Díaz, Seliem El-Sayed, Jaylen Pittman, Shakir Mohamed, Kevin R. McKee
The illusion of artificial inclusion. CoRR (2024)
Suman V. Ravuri, Mélanie Rey, Shakir Mohamed, Marc Peter Deisenroth
Understanding Deep Generative Models with Generalized Empirical Likelihoods. CoRR (2023)
Ilan Price, Alvaro Sanchez-Gonzalez, Ferran Alet, Timo Ewalds, Andrew El-Kadi, Jacklynn Stott, Shakir Mohamed, Peter W. Battaglia, Rémi Lam, Matthew Willson
GenCast: Diffusion-based ensemble forecasting for medium-range weather. CoRR (2023)
Suman V. Ravuri, Mélanie Rey, Shakir Mohamed, Marc Peter Deisenroth
Understanding Deep Generative Models with Generalized Empirical Likelihoods. CVPR (2023)
Marzyeh Ghassemi, Shakir Mohamed
Machine learning and health need better values. npj Digit. Medicine 5 (2022)
Lindiwe Brigitte Malobola, Negar Rostamzadeh, Shakir Mohamed
se-Shweshwe Inspired Fashion Generation. CoRR (2022)
Sanket Kamthe, So Takao, Shakir Mohamed, Marc Peter Deisenroth
Iterative State Estimation in Non-linear Dynamical Systems Using Approximate Expectation Propagation. Trans. Mach. Learn. Res. 2022 (2022)
Abeba Birhane, William Isaac, Vinodkumar Prabhakaran, Mark Diaz, Madeleine Clare Elish, Iason Gabriel, Shakir Mohamed
Power to the People? Opportunities and Challenges for Participatory AI. EAAMO (2022)
Abeba Birhane, William Isaac, Vinodkumar Prabhakaran, Mark Díaz, Madeleine Clare Elish, Iason Gabriel, Shakir Mohamed
Power to the People? Opportunities and Challenges for Participatory AI. CoRR (2022)
Rémi Lam, Alvaro Sanchez-Gonzalez, Matthew Willson, Peter Wirnsberger, Meire Fortunato, Alexander Pritzel, Suman V. Ravuri, Timo Ewalds, Ferran Alet, Zach Eaton-Rosen, Weihua Hu, Alexander Merose, Stephan Hoyer, George Holland, Jacklynn Stott, Oriol Vinyals, Shakir Mohamed, Peter W. Battaglia
GraphCast: Learning skillful medium-range global weather forecasting. CoRR (2022)
Suman V. Ravuri, Karel Lenc, Matthew Willson, Dmitry Kangin, Rémi Lam, Piotr Mirowski, Megan Fitzsimons, Maria Athanassiadou, Sheleem Kashem, Sam Madge, Rachel Prudden, Amol Mandhane, Aidan Clark, Andrew Brock, Karen Simonyan, Raia Hadsell, Niall H. Robinson, Ellen Clancy, Alberto Arribas, Shakir Mohamed
Skillful Precipitation Nowcasting using Deep Generative Models of Radar. CoRR (2021)
Nenad Tomasev, Kevin R. McKee, Jackie Kay, Shakir Mohamed
Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities. CoRR (2021)
Nenad Tomasev, Kevin R. McKee, Jackie Kay, Shakir Mohamed
Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities. AIES (2021)
Suman V. Ravuri, Karel Lenc, Matthew Willson, Dmitry Kangin, Rémi Lam, Piotr Mirowski, Megan Fitzsimons, Maria Athanassiadou, Sheleem Kashem, Sam Madge, Rachel Prudden, Amol Mandhane, Aidan Clark, Andrew Brock, Karen Simonyan, Raia Hadsell, Niall H. Robinson, Ellen Clancy, Alberto Arribas, Shakir Mohamed
Skilful precipitation nowcasting using deep generative models of radar. Nat. 597 (7878) (2021)
George Papamakarios, Eric T. Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan
Normalizing Flows for Probabilistic Modeling and Inference. J. Mach. Learn. Res. 22 (2021)
Shakir Mohamed
Domesticating the techno-racial project. Nat. Mach. Intell. 2 (9) (2020)
Shakir Mohamed, Marie-Therese Png, William Isaac
Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. CoRR (2020)
Shakir Mohamed, Mihaela Rosca, Michael Figurnov, Andriy Mnih
Monte Carlo Gradient Estimation in Machine Learning. J. Mach. Learn. Res. 21 (2020)
Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed
A case for new neural network smoothness constraints. CoRR (2020)
Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed
A case for new neural network smoothness constraints. ICBINB@NeurIPS (2020)
Rachel Prudden, Samantha V. Adams, Dmitry Kangin, Niall H. Robinson, Suman V. Ravuri, Shakir Mohamed, Alberto Arribas
A review of radar-based nowcasting of precipitation and applicable machine learning techniques. CoRR (2020)
Jessica B. Hamrick, Shakir Mohamed
Levels of Analysis for Machine Learning. CoRR (2020)
Shakir Mohamed, Mihaela Rosca, Michael Figurnov, Andriy Mnih
Monte Carlo Gradient Estimation in Machine Learning. CoRR (2019)
Cyprien de Masson d'Autume, Mihaela Rosca, Jack W. Rae, Shakir Mohamed
Training language GANs from Scratch. CoRR (2019)
George Papamakarios, Eric T. Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan
Normalizing Flows for Probabilistic Modeling and Inference. CoRR (2019)
Cyprien de Masson d'Autume, Shakir Mohamed, Mihaela Rosca, Jack W. Rae
Training Language GANs from Scratch. NeurIPS (2019)
Mihaela Rosca, Balaji Lakshminarayanan, Shakir Mohamed
Distribution Matching in Variational Inference. CoRR (2018)
Mikhail Figurnov, Shakir Mohamed, Andriy Mnih
Implicit Reparameterization Gradients. NeurIPS (2018)
Suman V. Ravuri, Shakir Mohamed, Mihaela Rosca, Oriol Vinyals
Learning Implicit Generative Models with the Method of Learned Moments. ICML (2018)
William Fedus, Mihaela Rosca, Balaji Lakshminarayanan, Andrew M. Dai, Shakir Mohamed, Ian J. Goodfellow
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step. ICLR (Poster) (2018)
Michael Figurnov, Shakir Mohamed, Andriy Mnih
Implicit Reparameterization Gradients. CoRR (2018)
Greg Wayne, Chia-Chun Hung, David Amos, Mehdi Mirza, Arun Ahuja, Agnieszka Grabska-Barwinska, Jack W. Rae, Piotr Mirowski, Joel Z. Leibo, Adam Santoro, Mevlana Gemici, Malcolm Reynolds, Tim Harley, Josh Abramson, Shakir Mohamed, Danilo Jimenez Rezende, David Saxton, Adam Cain, Chloe Hillier, David Silver, Koray Kavukcuoglu, Matthew Botvinick, Demis Hassabis, Timothy P. Lillicrap
Unsupervised Predictive Memory in a Goal-Directed Agent. CoRR (2018)
Suman V. Ravuri, Shakir Mohamed, Mihaela Rosca, Oriol Vinyals
Learning Implicit Generative Models with the Method of Learned Moments. CoRR (2018)
Mihaela Rosca, Balaji Lakshminarayanan, David Warde-Farley, Shakir Mohamed
Variational Approaches for Auto-Encoding Generative Adversarial Networks. CoRR (2017)
Marc G. Bellemare, Ivo Danihelka, Will Dabney, Shakir Mohamed, Balaji Lakshminarayanan, Stephan Hoyer, Rémi Munos
The Cramer Distance as a Solution to Biased Wasserstein Gradients. CoRR (2017)
Silvia Chiappa, Sébastien Racanière, Daan Wierstra, Shakir Mohamed
Recurrent Environment Simulators. CoRR (2017)
Mevlana Gemici, Chia-Chun Hung, Adam Santoro, Greg Wayne, Shakir Mohamed, Danilo Jimenez Rezende, David Amos, Timothy P. Lillicrap
Generative Temporal Models with Memory. CoRR (2017)
Irina Higgins, Loïc Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, Alexander Lerchner
beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework. ICLR (Poster) (2017)
William Fedus, Mihaela Rosca, Balaji Lakshminarayanan, Andrew M. Dai, Shakir Mohamed, Ian J. Goodfellow
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step. CoRR (2017)
Silvia Chiappa, Sébastien Racanière, Daan Wierstra, Shakir Mohamed
Recurrent Environment Simulators. ICLR (Poster) (2017)
Mevlana C. Gemici, Danilo Jimenez Rezende, Shakir Mohamed
Normalizing Flows on Riemannian Manifolds. CoRR (2016)
Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra
One-Shot Generalization in Deep Generative Models. ICML (2016)
Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra
One-Shot Generalization in Deep Generative Models. CoRR (2016)
Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter W. Battaglia, Max Jaderberg, Nicolas Heess
Unsupervised Learning of 3D Structure from Images. CoRR (2016)
Irina Higgins, Loïc Matthey, Xavier Glorot, Arka Pal, Benigno Uria, Charles Blundell, Shakir Mohamed, Alexander Lerchner
Early Visual Concept Learning with Unsupervised Deep Learning. CoRR (2016)
Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter W. Battaglia, Max Jaderberg, Nicolas Heess
Unsupervised Learning of 3D Structure from Images. NIPS (2016)
Shakir Mohamed, Balaji Lakshminarayanan
Learning in Implicit Generative Models. CoRR (2016)
Danilo Jimenez Rezende, Shakir Mohamed
Variational Inference with Normalizing Flows. CoRR (2015)
Shakir Mohamed, Danilo Jimenez Rezende
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning. CoRR (2015)
Danilo Jimenez Rezende, Shakir Mohamed
Variational Inference with Normalizing Flows. ICML (2015)
Shakir Mohamed, Danilo Jimenez Rezende
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning. NIPS (2015)
Diederik P. Kingma, Shakir Mohamed, Danilo Jimenez Rezende, Max Welling
Semi-supervised Learning with Deep Generative Models. NIPS (2014)
Diederik P. Kingma, Danilo Jimenez Rezende, Shakir Mohamed, Max Welling
Semi-Supervised Learning with Deep Generative Models. CoRR (2014)
Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra
Stochastic Back-propagation and Variational Inference in Deep Latent Gaussian Models. CoRR (2014)
Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra
Stochastic Backpropagation and Approximate Inference in Deep Generative Models. ICML (2014)
Ziyu Wang, Shakir Mohamed, Nando de Freitas
Adaptive Hamiltonian and Riemann Manifold Monte Carlo. ICML (3) (2013)
Mohammad Emtiyaz Khan, Shakir Mohamed, Kevin P. Murphy
Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression. NIPS (2012)
Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani
Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning . ICML (2012)
Marc Peter Deisenroth, Shakir Mohamed
Expectation Propagation in Gaussian Process Dynamical Systems CoRR (2012)
Marc Peter Deisenroth, Shakir Mohamed
Expectation Propagation in Gaussian Process Dynamical Systems. NIPS (2012)
David Buchman, Mark Schmidt, Shakir Mohamed, David Poole, Nando de Freitas
On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models. AISTATS (2012)
Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M. Marlin, Kevin P. Murphy
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models. AISTATS (2012)
Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani
Bayesian and L1 Approaches to Sparse Unsupervised Learning CoRR (2011)
Finale Doshi-Velez, David A. Knowles, Shakir Mohamed, Zoubin Ghahramani
Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process. NIPS (2009)
Mikkel N. Schmidt, Shakir Mohamed
Probabilistic non-negative tensor factorization using Markov chain Monte Carlo. EUSIPCO (2009)
Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani
Bayesian Exponential Family PCA. NIPS (2008)
Shakir Mohamed, David M. Rubin, Tshilidzi Marwala
Incremental Learning for Classification of Protein Sequences. IJCNN (2007)
Shakir Mohamed, David M. Rubin, Tshilidzi Marwala
An Adaptive Strategy for the Classification of G-Protein Coupled Receptors CoRR (2007)
Shakir Mohamed, Thando Tettey, Tshilidzi Marwala
An Extension Neural Network and Genetic Algorithm for Bearing Fault Classification. IJCNN (2006)
Shakir Mohamed, David M. Rubin, Tshilidzi Marwala
Multi-class Protein Sequence Classification Using Fuzzy ARTMAP. SMC (2006)

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Publication Activity (10 Years)

Top Topics

Top Venues

Shakir Mohamed