default search action
Shakir Mohamed
Person information
- affiliation: DeepMind, UK
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [c30]William Agnew
, A. Stevie Bergman
The Illusion of Artificial Inclusion. CHI 2024: 286:1-286:12 - [c29]Piotr Mirowski
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: 1622-1636 - [i40]William Agnew, A. Stevie Bergman, Jennifer Chien, Mark Díaz, Seliem El-Sayed, Jaylen Pittman
The illusion of artificial inclusion. CoRR abs/2401.08572 (2024) - [i39]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 abs/2405.20956 (2024) - [i38]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 abs/2407.11666 (2024) - [i37]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 abs/2407.12687 (2024) - [i36]Jackie Kay, Atoosa Kasirzadeh, Shakir Mohamed:
Epistemic Injustice in Generative AI. CoRR abs/2408.11441 (2024) - 2023
- [c28]Suman V. Ravuri, Mélanie Rey, Shakir Mohamed, Marc Peter Deisenroth:
Understanding Deep Generative Models with Generalized Empirical Likelihoods. CVPR 2023: 24395-24405 - [i35]Suman V. Ravuri, Mélanie Rey, Shakir Mohamed, Marc Peter Deisenroth:
Understanding Deep Generative Models with Generalized Empirical Likelihoods. CoRR abs/2306.09780 (2023) - [i34]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 abs/2312.15796 (2023) - 2022
- [j6]Marzyeh Ghassemi
Machine learning and health need better values. npj Digit. Medicine 5 (2022) - [j5]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) - [c27]Abeba Birhane, William Isaac, Vinodkumar Prabhakaran, Mark Diaz, Madeleine Clare Elish, Iason Gabriel
Power to the People? Opportunities and Challenges for Participatory AI. EAAMO 2022: 6:1-6:8 - [i33]Lindiwe Brigitte Malobola, Negar Rostamzadeh, Shakir Mohamed:
se-Shweshwe Inspired Fashion Generation. CoRR abs/2203.00435 (2022) - [i32]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 abs/2209.07572 (2022) - [i31]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 abs/2212.12794 (2022) - 2021
- [j4]George Papamakarios, Eric T. Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan:
Normalizing Flows for Probabilistic Modeling and Inference. J. Mach. Learn. Res. 22: 57:1-57:64 (2021) - [j3]Suman V. Ravuri
Skilful precipitation nowcasting using deep generative models of radar. Nat. 597(7878): 672-677 (2021) - [c26]Nenad Tomasev, Kevin R. McKee
Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities. AIES 2021: 254-265 - [i30]Nenad Tomasev, Kevin R. McKee, Jackie Kay, Shakir Mohamed:
Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities. CoRR abs/2102.04257 (2021) - [i29]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 abs/2104.00954 (2021) - 2020
- [j2]Shakir Mohamed, Mihaela Rosca, Michael Figurnov, Andriy Mnih:
Monte Carlo Gradient Estimation in Machine Learning. J. Mach. Learn. Res. 21: 132:1-132:62 (2020) - [j1]Shakir Mohamed
Domesticating the techno-racial project. Nat. Mach. Intell. 2(9): 491 (2020) - [c25]Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed:
A case for new neural network smoothness constraints. ICBINB@NeurIPS 2020: 21-32 - [i28]Jessica B. Hamrick, Shakir Mohamed:
Levels of Analysis for Machine Learning. CoRR abs/2004.05107 (2020) - [i27]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 abs/2005.04988 (2020) - [i26]Shakir Mohamed, Marie-Therese Png, William Isaac:
Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. CoRR abs/2007.04068 (2020) - [i25]Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed:
A case for new neural network smoothness constraints. CoRR abs/2012.07969 (2020)
2010 – 2019
- 2019
- [c24]Cyprien de Masson d'Autume, Shakir Mohamed, Mihaela Rosca, Jack W. Rae:
Training Language GANs from Scratch. NeurIPS 2019: 4302-4313 - [i24]Cyprien de Masson d'Autume, Mihaela Rosca, Jack W. Rae, Shakir Mohamed:
Training language GANs from Scratch. CoRR abs/1905.09922 (2019) - [i23]Shakir Mohamed, Mihaela Rosca, Michael Figurnov, Andriy Mnih:
Monte Carlo Gradient Estimation in Machine Learning. CoRR abs/1906.10652 (2019) - [i22]George Papamakarios, Eric T. Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan:
Normalizing Flows for Probabilistic Modeling and Inference. CoRR abs/1912.02762 (2019) - 2018
- [c23]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 - [c22]Suman V. Ravuri, Shakir Mohamed, Mihaela Rosca, Oriol Vinyals:
Learning Implicit Generative Models with the Method of Learned Moments. ICML 2018: 4311-4320 - [c21]Mikhail Figurnov, Shakir Mohamed, Andriy Mnih:
Implicit Reparameterization Gradients. NeurIPS 2018: 439-450 - [i21]Mihaela Rosca, Balaji Lakshminarayanan, Shakir Mohamed:
Distribution Matching in Variational Inference. CoRR abs/1802.06847 (2018) - [i20]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:
Unsupervised Predictive Memory in a Goal-Directed Agent. CoRR abs/1803.10760 (2018) - [i19]Michael Figurnov, Shakir Mohamed, Andriy Mnih:
Implicit Reparameterization Gradients. CoRR abs/1805.08498 (2018) - [i18]Suman V. Ravuri, Shakir Mohamed, Mihaela Rosca, Oriol Vinyals:
Learning Implicit Generative Models with the Method of Learned Moments. CoRR abs/1806.11006 (2018) - 2017
- [c20]Silvia Chiappa, Sébastien Racanière, Daan Wierstra, Shakir Mohamed:
Recurrent Environment Simulators. ICLR (Poster) 2017 - [c19]Irina Higgins, Loïc Matthey, Arka Pal, Christopher P. Burgess, Xavier Glorot
beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework. ICLR (Poster) 2017 - [i17]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 abs/1702.04649 (2017) - [i16]Silvia Chiappa, Sébastien Racanière, Daan Wierstra, Shakir Mohamed:
Recurrent Environment Simulators. CoRR abs/1704.02254 (2017) - [i15]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 abs/1705.10743 (2017) - [i14]Mihaela Rosca, Balaji Lakshminarayanan, David Warde-Farley, Shakir Mohamed:
Variational Approaches for Auto-Encoding Generative Adversarial Networks. CoRR abs/1706.04987 (2017) - [i13]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 abs/1710.08446 (2017) - 2016
- [c18]Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra:
One-Shot Generalization in Deep Generative Models. ICML 2016: 1521-1529 - [c17]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: 4997-5005 - [i12]Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra:
One-Shot Generalization in Deep Generative Models. CoRR abs/1603.05106 (2016) - [i11]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 abs/1606.05579 (2016) - [i10]Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter W. Battaglia, Max Jaderberg, Nicolas Heess:
Unsupervised Learning of 3D Structure from Images. CoRR abs/1607.00662 (2016) - [i9]Shakir Mohamed, Balaji Lakshminarayanan:
Learning in Implicit Generative Models. CoRR abs/1610.03483 (2016) - [i8]Mevlana C. Gemici, Danilo Jimenez Rezende, Shakir Mohamed:
Normalizing Flows on Riemannian Manifolds. CoRR abs/1611.02304 (2016) - 2015
- [c16]Danilo Jimenez Rezende, Shakir Mohamed:
Variational Inference with Normalizing Flows. ICML 2015: 1530-1538 - [c15]Shakir Mohamed, Danilo Jimenez Rezende:
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning. NIPS 2015: 2125-2133 - [i7]Danilo Jimenez Rezende, Shakir Mohamed:
Variational Inference with Normalizing Flows. CoRR abs/1505.05770 (2015) - [i6]Shakir Mohamed, Danilo Jimenez Rezende:
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning. CoRR abs/1509.08731 (2015) - 2014
- [c14]Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra:
Stochastic Backpropagation and Approximate Inference in Deep Generative Models. ICML 2014: 1278-1286 - [c13]Diederik P. Kingma, Shakir Mohamed, Danilo Jimenez Rezende, Max Welling:
Semi-supervised Learning with Deep Generative Models. NIPS 2014: 3581-3589 - [r1]Zoubin Ghahramani, Shakir Mohamed, Katherine A. Heller:
Partial Membership and Factor Analysis. Handbook of Mixed Membership Models and Their Applications 2014: 67-88 - [i5]Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra:
Stochastic Back-propagation and Variational Inference in Deep Latent Gaussian Models. CoRR abs/1401.4082 (2014) - [i4]Diederik P. Kingma, Danilo Jimenez Rezende, Shakir Mohamed, Max Welling:
Semi-Supervised Learning with Deep Generative Models. CoRR abs/1406.5298 (2014) - 2013
- [c12]Ziyu Wang, Shakir Mohamed, Nando de Freitas:
Adaptive Hamiltonian and Riemann Manifold Monte Carlo. ICML (3) 2013: 1462-1470 - 2012
- [c11]Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani:
Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning . ICML 2012 - [c10]Marc Peter Deisenroth, Shakir Mohamed:
Expectation Propagation in Gaussian Process Dynamical Systems. NIPS 2012: 2618-2626 - [c9]Mohammad Emtiyaz Khan, Shakir Mohamed, Kevin P. Murphy:
Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression. NIPS 2012: 3149-3157 - [c8]David Buchman, Mark Schmidt, Shakir Mohamed, David Poole, Nando de Freitas:
On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models. AISTATS 2012: 173-181 - [c7]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: 610-618 - [i3]Marc Peter Deisenroth, Shakir Mohamed:
Expectation Propagation in Gaussian Process Dynamical Systems. CoRR abs/1207.2940 (2012) - 2011
- [b1]Shakir Mohamed:
Generalised Bayesian matrix factorisation models. University of Cambridge, UK, 2011 - [i2]Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani:
Bayesian and L1 Approaches to Sparse Unsupervised Learning. CoRR abs/1106.1157 (2011)
2000 – 2009
- 2009
- [c6]Mikkel N. Schmidt, Shakir Mohamed:
Probabilistic non-negative tensor factorization using Markov chain Monte Carlo. EUSIPCO 2009: 1918-1922 - [c5]Finale Doshi-Velez, David A. Knowles, Shakir Mohamed, Zoubin Ghahramani:
Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process. NIPS 2009: 1294-1302 - 2008
- [c4]Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani:
Bayesian Exponential Family PCA. NIPS 2008: 1089-1096 - 2007
- [c3]Shakir Mohamed, David M. Rubin
Incremental Learning for Classification of Protein Sequences. IJCNN 2007: 19-24 - [i1]Shakir Mohamed, David M. Rubin, Tshilidzi Marwala:
An Adaptive Strategy for the Classification of G-Protein Coupled Receptors. CoRR abs/0704.3453 (2007) - 2006
- [c2]Shakir Mohamed, Thando Tettey, Tshilidzi Marwala:
An Extension Neural Network and Genetic Algorithm for Bearing Fault Classification. IJCNN 2006: 3942-3948 - [c1]Shakir Mohamed, David M. Rubin
Multi-class Protein Sequence Classification Using Fuzzy ARTMAP. SMC 2006: 1676-1681
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-09-28 01:29 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: