Shakir Mohamed

82 papers A* 9A 2B 3C 1Journal 49Unranked 16

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	AI tutoring can safely and effectively support students: An exploratory RCT in UK classrooms. CoRR LearnLM Team Google, Albert Wang, Aliya Rysbek, Andrea Huber, Anjali Nambiar, Anna Kenolty, Ben Caulfield, Beth Lilley-Draper, Bibi Groot, Brian Veprek, Chelsea Burdett, Claire Willis, Craig Barton, Digory Smith, George Mu, Harriet Walters, Irina Jurenka, Iris Hulls, James Stalley-Moores, Jonathan Caton, Julia Wilkowski, Kaiz Alarakyia, Kevin R. McKee, Liam McCafferty, Lucy Dalton, Markus Kunesch, Pauline Malubay, Rachel Kidson, Rich Wells, Sam Wheeler, Sara Wiltberger, Shakir Mohamed, Simon Woodhead, Vasco Brazão
2025	J	`jnl`	Contextualizing ancient texts with generative neural networks. Nat. Yannis M. Assael, Thea Sommerschield, Alison Cooley, Brendan Shillingford, John Pavlopoulos, Priyanka Suresh, Bailey Herms, Justin Grayston, Benjamin Maynard, Nicholas Dietrich, Robbe Wulgaert, Jonathan Prag, Alex Mullen, Shakir Mohamed
2025	J	`jnl`	Probabilistic weather forecasting with machine learning. Nat. Ilan Price, Alvaro Sanchez-Gonzalez, Ferran Alet, Tom R. Andersson, Andrew El-Kadi, Dominic Masters, Timo Ewalds, Jacklynn Stott, Shakir Mohamed, Peter W. Battaglia, Rémi R. Lam, Matthew Willson
2024	J	`jnl`	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 Piotr W. Mirowski, Juliette Love, Kory W. Mathewson, Shakir Mohamed
2024	—	`conf`	A Robot Walks into a Bar: Can Language Models Serve as Creativity SupportTools for Comedy? An Evaluation of LLMs' Humour Alignment with Comedians. FAccT Piotr Mirowski, Juliette Love, Kory W. Mathewson, Shakir Mohamed
2024	—	`conf`	Epistemic Injustice in Generative AI. AIES (1) Jackie Kay, Atoosa Kasirzadeh, Shakir Mohamed
2024	J	`jnl`	Epistemic Injustice in Generative AI. CoRR Jackie Kay, Atoosa Kasirzadeh, Shakir Mohamed
2024	J	`jnl`	Neural Compression of Atmospheric States. CoRR Piotr Mirowski, David Warde-Farley, Mihaela Rosca, Matthew Koichi Grimes, Yana Hasson, Hyunjik Kim, Mélanie Rey, Simon Osindero, Suman V. Ravuri, Shakir Mohamed
2024	A*	`conf`	The Illusion of Artificial Inclusion. CHI William Agnew, A. Stevie Bergman, Jennifer Chien, Mark Díaz, Seliem El-Sayed, Jaylen Pittman, Shakir Mohamed, Kevin R. McKee
2024	J	`jnl`	The illusion of artificial inclusion. CoRR William Agnew, A. Stevie Bergman, Jennifer Chien, Mark Díaz, Seliem El-Sayed, Jaylen Pittman, Shakir Mohamed, Kevin R. McKee
2024	J	`jnl`	Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach. CoRR 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 Strinopoulos, Annie Hale, Wayne Anderson, Luis C. Cobo, Niv Efron, Muktha Ananda, Shakir Mohamed, Maureen Heymans, Zoubin Ghahramani, Yossi Matias, Ben Gomes, Lila Ibrahim
2023	J	`jnl`	GenCast: Diffusion-based ensemble forecasting for medium-range weather. CoRR Ilan Price, Alvaro Sanchez-Gonzalez, Ferran Alet, Timo Ewalds, Andrew El-Kadi, Jacklynn Stott, Shakir Mohamed, Peter W. Battaglia, Rémi Lam, Matthew Willson
2023	A*	`conf`	Understanding Deep Generative Models with Generalized Empirical Likelihoods. CVPR Suman V. Ravuri, Mélanie Rey, Shakir Mohamed, Marc Peter Deisenroth
2023	J	`jnl`	Understanding Deep Generative Models with Generalized Empirical Likelihoods. CoRR Suman V. Ravuri, Mélanie Rey, Shakir Mohamed, Marc Peter Deisenroth
2022	J	`jnl`	GraphCast: Learning skillful medium-range global weather forecasting. CoRR 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
2022	J	`jnl`	Iterative State Estimation in Non-linear Dynamical Systems Using Approximate Expectation Propagation. Trans. Mach. Learn. Res. Sanket Kamthe, So Takao, Shakir Mohamed, Marc Peter Deisenroth
2022	J	`jnl`	Machine learning and health need better values. npj Digit. Medicine Marzyeh Ghassemi, Shakir Mohamed
2022	—	`conf`	Power to the People? Opportunities and Challenges for Participatory AI. EAAMO Abeba Birhane, William Isaac, Vinodkumar Prabhakaran, Mark Diaz, Madeleine Clare Elish, Iason Gabriel, Shakir Mohamed
2022	J	`jnl`	Power to the People? Opportunities and Challenges for Participatory AI. CoRR Abeba Birhane, William Isaac, Vinodkumar Prabhakaran, Mark Díaz, Madeleine Clare Elish, Iason Gabriel, Shakir Mohamed
2022	J	`jnl`	se-Shweshwe Inspired Fashion Generation. CoRR Lindiwe Brigitte Malobola, Negar Rostamzadeh, Shakir Mohamed
2021	C	`conf`	Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities. AIES Nenad Tomasev, Kevin R. McKee, Jackie Kay, Shakir Mohamed
2021	J	`jnl`	Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities. CoRR Nenad Tomasev, Kevin R. McKee, Jackie Kay, Shakir Mohamed
2021	J	`jnl`	Normalizing Flows for Probabilistic Modeling and Inference. J. Mach. Learn. Res. George Papamakarios, Eric T. Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan
2021	J	`jnl`	Skilful precipitation nowcasting using deep generative models of radar. Nat. 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
2021	J	`jnl`	Skillful Precipitation Nowcasting using Deep Generative Models of Radar. CoRR 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
2020	—	`conf`	A case for new neural network smoothness constraints. ICBINB@NeurIPS Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed
2020	J	`jnl`	A case for new neural network smoothness constraints. CoRR Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed
2020	J	`jnl`	A review of radar-based nowcasting of precipitation and applicable machine learning techniques. CoRR Rachel Prudden, Samantha V. Adams, Dmitry Kangin, Niall H. Robinson, Suman V. Ravuri, Shakir Mohamed, Alberto Arribas
2020	J	`jnl`	Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. CoRR Shakir Mohamed, Marie-Therese Png, William Isaac
2020	J	`jnl`	Domesticating the techno-racial project. Nat. Mach. Intell. Shakir Mohamed
2020	J	`jnl`	Levels of Analysis for Machine Learning. CoRR Jessica B. Hamrick, Shakir Mohamed
2020	J	`jnl`	Monte Carlo Gradient Estimation in Machine Learning. J. Mach. Learn. Res. Shakir Mohamed, Mihaela Rosca, Michael Figurnov, Andriy Mnih
2019	J	`jnl`	Monte Carlo Gradient Estimation in Machine Learning. CoRR Shakir Mohamed, Mihaela Rosca, Michael Figurnov, Andriy Mnih
2019	J	`jnl`	Normalizing Flows for Probabilistic Modeling and Inference. CoRR George Papamakarios, Eric T. Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan
2019	A*	`conf`	Training Language GANs from Scratch. NeurIPS Cyprien de Masson d'Autume, Shakir Mohamed, Mihaela Rosca, Jack W. Rae
2019	J	`jnl`	Training language GANs from Scratch. CoRR Cyprien de Masson d'Autume, Mihaela Rosca, Jack W. Rae, Shakir Mohamed
2018	J	`jnl`	Distribution Matching in Variational Inference. CoRR Mihaela Rosca, Balaji Lakshminarayanan, Shakir Mohamed
2018	A*	`conf`	Implicit Reparameterization Gradients. NeurIPS Mikhail Figurnov, Shakir Mohamed, Andriy Mnih
2018	J	`jnl`	Implicit Reparameterization Gradients. CoRR Michael Figurnov, Shakir Mohamed, Andriy Mnih
2018	A*	`conf`	Learning Implicit Generative Models with the Method of Learned Moments. ICML Suman V. Ravuri, Shakir Mohamed, Mihaela Rosca, Oriol Vinyals
2018	J	`jnl`	Learning Implicit Generative Models with the Method of Learned Moments. CoRR Suman V. Ravuri, Shakir Mohamed, Mihaela Rosca, Oriol Vinyals
2018	—	`conf`	Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step. ICLR (Poster) William Fedus, Mihaela Rosca, Balaji Lakshminarayanan, Andrew M. Dai, Shakir Mohamed, Ian J. Goodfellow
2018	J	`jnl`	Unsupervised Predictive Memory in a Goal-Directed Agent. CoRR 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 M. Botvinick, Demis Hassabis, Timothy P. Lillicrap
2017	J	`jnl`	Generative Temporal Models with Memory. CoRR Mevlana Gemici, Chia-Chun Hung, Adam Santoro, Greg Wayne, Shakir Mohamed, Danilo Jimenez Rezende, David Amos, Timothy P. Lillicrap
2017	J	`jnl`	Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step. CoRR William Fedus, Mihaela Rosca, Balaji Lakshminarayanan, Andrew M. Dai, Shakir Mohamed, Ian J. Goodfellow
2017	—	`conf`	Recurrent Environment Simulators. ICLR (Poster) Silvia Chiappa, Sébastien Racanière, Daan Wierstra, Shakir Mohamed
2017	J	`jnl`	Recurrent Environment Simulators. CoRR Silvia Chiappa, Sébastien Racanière, Daan Wierstra, Shakir Mohamed
2017	J	`jnl`	The Cramer Distance as a Solution to Biased Wasserstein Gradients. CoRR Marc G. Bellemare, Ivo Danihelka, Will Dabney, Shakir Mohamed, Balaji Lakshminarayanan, Stephan Hoyer, Rémi Munos
2017	J	`jnl`	Variational Approaches for Auto-Encoding Generative Adversarial Networks. CoRR Mihaela Rosca, Balaji Lakshminarayanan, David Warde-Farley, Shakir Mohamed
2017	—	`conf`	beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework. ICLR (Poster) Irina Higgins, Loïc Matthey, Arka Pal, Christopher P. Burgess, Xavier Glorot, Matthew M. Botvinick, Shakir Mohamed, Alexander Lerchner
2016	J	`jnl`	Early Visual Concept Learning with Unsupervised Deep Learning. CoRR Irina Higgins, Loïc Matthey, Xavier Glorot, Arka Pal, Benigno Uria, Charles Blundell, Shakir Mohamed, Alexander Lerchner
2016	J	`jnl`	Learning in Implicit Generative Models. CoRR Shakir Mohamed, Balaji Lakshminarayanan
2016	J	`jnl`	Normalizing Flows on Riemannian Manifolds. CoRR Mevlana C. Gemici, Danilo Jimenez Rezende, Shakir Mohamed
2016	A*	`conf`	One-Shot Generalization in Deep Generative Models. ICML Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra
2016	J	`jnl`	One-Shot Generalization in Deep Generative Models. CoRR Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra
2016	—	`conf`	Unsupervised Learning of 3D Structure from Images. NIPS Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter W. Battaglia, Max Jaderberg, Nicolas Heess
2016	J	`jnl`	Unsupervised Learning of 3D Structure from Images. CoRR Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter W. Battaglia, Max Jaderberg, Nicolas Heess
2015	A*	`conf`	Variational Inference with Normalizing Flows. ICML Danilo Jimenez Rezende, Shakir Mohamed
2015	J	`jnl`	Variational Inference with Normalizing Flows. CoRR Danilo Jimenez Rezende, Shakir Mohamed
2015	—	`conf`	Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning. NIPS Shakir Mohamed, Danilo Jimenez Rezende
2015	J	`jnl`	Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning. CoRR Shakir Mohamed, Danilo Jimenez Rezende
2014	—	`ch.`	Partial Membership and Factor Analysis. Handbook of Mixed Membership Models and Their Applications Zoubin Ghahramani, Shakir Mohamed, Katherine A. Heller
2014	J	`jnl`	Semi-Supervised Learning with Deep Generative Models. CoRR Diederik P. Kingma, Danilo Jimenez Rezende, Shakir Mohamed, Max Welling
2014	—	`conf`	Semi-supervised Learning with Deep Generative Models. NIPS Diederik P. Kingma, Shakir Mohamed, Danilo Jimenez Rezende, Max Welling
2014	J	`jnl`	Stochastic Back-propagation and Variational Inference in Deep Latent Gaussian Models. CoRR Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra
2014	A*	`conf`	Stochastic Backpropagation and Approximate Inference in Deep Generative Models. ICML Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra
2013	—	`conf`	Adaptive Hamiltonian and Riemann Manifold Monte Carlo. ICML (3) Ziyu Wang, Shakir Mohamed, Nando de Freitas
2012	A	`conf`	A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models. AISTATS Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M. Marlin, Kevin P. Murphy
2012	A*	`conf`	Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning . ICML Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani
2012	J	`jnl`	Expectation Propagation in Gaussian Process Dynamical Systems CoRR Marc Peter Deisenroth, Shakir Mohamed
2012	—	`conf`	Expectation Propagation in Gaussian Process Dynamical Systems. NIPS Marc Peter Deisenroth, Shakir Mohamed
2012	—	`conf`	Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression. NIPS Mohammad Emtiyaz Khan, Shakir Mohamed, Kevin P. Murphy
2012	A	`conf`	On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models. AISTATS David Buchman, Mark Schmidt, Shakir Mohamed, David Poole, Nando de Freitas
2011	J	`jnl`	Bayesian and L1 Approaches to Sparse Unsupervised Learning CoRR Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani
2011	—	`—`	Generalised Bayesian matrix factorisation models. Shakir Mohamed
2009	—	`conf`	Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process. NIPS Finale Doshi-Velez, David A. Knowles, Shakir Mohamed, Zoubin Ghahramani
2009	—	`conf`	Probabilistic non-negative tensor factorization using Markov chain Monte Carlo. EUSIPCO Mikkel N. Schmidt, Shakir Mohamed
2008	—	`conf`	Bayesian Exponential Family PCA. NIPS Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani
2007	J	`jnl`	An Adaptive Strategy for the Classification of G-Protein Coupled Receptors CoRR Shakir Mohamed, David M. Rubin, Tshilidzi Marwala
2007	B	`conf`	Incremental Learning for Classification of Protein Sequences. IJCNN Shakir Mohamed, David M. Rubin, Tshilidzi Marwala
2006	B	`conf`	An Extension Neural Network and Genetic Algorithm for Bearing Fault Classification. IJCNN Shakir Mohamed, Thando Tettey, Tshilidzi Marwala
2006	B	`conf`	Multi-class Protein Sequence Classification Using Fuzzy ARTMAP. SMC Shakir Mohamed, David M. Rubin, Tshilidzi Marwala