default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDPushmeet Kohli
Person information
- affiliation: Deepmind, London, UK
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j43]Bernardino Romera-Paredes
, Mohammadamin Barekatain, Alexander Novikov, Matej Balog, M. Pawan Kumar, Emilien Dupont, Francisco J. R. Ruiz, Jordan S. Ellenberg, Pengming Wang, Omar Fawzi, Pushmeet Kohli, Alhussein Fawzi:
Mathematical discoveries from program search with large language models. Nat. 625(7995): 468-475 (2024)- [i108]Francisco J. R. Ruiz, Tuomas Laakkonen, Johannes Bausch, Matej Balog, Mohammadamin Barekatain, Francisco J. H. Heras, Alexander Novikov, Nathan Fitzpatrick, Bernardino Romera-Paredes, John van de Wetering, Alhussein Fawzi, Konstantinos Meichanetzidis, Pushmeet Kohli:
Quantum Circuit Optimization with AlphaTensor. CoRR abs/2402.14396 (2024) - [i107]Sahra Ghalebikesabi, Eugene Bagdasaryan, Ren Yi, Itay Yona, Ilia Shumailov, Aneesh Pappu, Chongyang Shi, Laura Weidinger, Robert Stanforth, Leonard Berrada, Pushmeet Kohli, Po-Sen Huang, Borja Balle:
Operationalizing Contextual Integrity in Privacy-Conscious Assistants. CoRR abs/2408.02373 (2024) - 2023
- [j42]Daniel J. Mankowitz, Andrea Michi, Anton Zhernov, Marco Gelmi, Marco Selvi, Cosmin Paduraru, Edouard Leurent, Shariq Iqbal, Jean-Baptiste Lespiau, Alex Ahern, Thomas Köppe, Kevin Millikin, Stephen Gaffney, Sophie Elster, Jackson Broshear, Chris Gamble, Kieran Milan, Robert Tung, Minjae Hwang, A. Taylan Cemgil, Mohammadamin Barekatain, Yujia Li, Amol Mandhane, Thomas Hubert, Julian Schrittwieser, Demis Hassabis, Pushmeet Kohli, Martin A. Riedmiller, Oriol Vinyals, David Silver:
Faster sorting algorithms discovered using deep reinforcement learning. Nat. 618(7964): 257-263 (2023) - [j41]Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik:
Scientific discovery in the age of artificial intelligence. Nat. 620(7972): 47-60 (2023) - [i106]Ira Ktena, Olivia Wiles, Isabela Albuquerque, Sylvestre-Alvise Rebuffi, Ryutaro Tanno, Abhijit Guha Roy, Shekoofeh Azizi, Danielle Belgrave, Pushmeet Kohli, Alan Karthikesalingam, A. Taylan Cemgil, Sven Gowal:
Generative models improve fairness of medical classifiers under distribution shifts. CoRR abs/2304.09218 (2023) - [i105]David Stutz, Ali Taylan Cemgil, Abhijit Guha Roy, Tatiana Matejovicova, Melih Barsbey, Patricia Strachan, Mike Schaekermann, Jan Freyberg, Rajeev V. Rikhye, Beverly Freeman, Javier Perez Matos, Umesh Telang, Dale R. Webster, Yuan Liu, Gregory S. Corrado, Yossi Matias, Pushmeet Kohli, Yun Liu, Arnaud Doucet, Alan Karthikesalingam:
Evaluating AI systems under uncertain ground truth: a case study in dermatology. CoRR abs/2307.02191 (2023) - [i104]Leonard Berrada, Soham De, Judy Hanwen Shen, Jamie Hayes, Robert Stanforth, David Stutz, Pushmeet Kohli, Samuel L. Smith, Borja Balle:
Unlocking Accuracy and Fairness in Differentially Private Image Classification. CoRR abs/2308.10888 (2023) - [i103]Johannes Bausch, Andrew W. Senior, Francisco J. H. Heras, Thomas Edlich, Alex Davies, Michael Newman, Cody Jones, Kevin J. Satzinger, Murphy Yuezhen Niu, Sam Blackwell, George Holland, Dvir Kafri, Juan Atalaya, Craig Gidney, Demis Hassabis, Sergio Boixo, Hartmut Neven, Pushmeet Kohli:
Learning to Decode the Surface Code with a Recurrent, Transformer-Based Neural Network. CoRR abs/2310.05900 (2023) - [i102]Ryutaro Tanno, David G. T. Barrett, Andrew Sellergren, Sumedh Ghaisas, Sumanth Dathathri, Abigail See, Johannes Welbl, Karan Singhal, Shekoofeh Azizi, Tao Tu, Mike Schaekermann, Rhys May, Roy Lee, SiWai Man, Zahra Ahmed, S. Sara Mahdavi, Danielle Belgrave, Vivek Natarajan, Shravya Shetty, Pushmeet Kohli, Po-Sen Huang, Alan Karthikesalingam, Ira Ktena:
Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation. CoRR abs/2311.18260 (2023) - 2022
- [j40]Mihaly Varadi, Stephen Anyango, Mandar S. Deshpande, Sreenath Nair, Cindy Natassia, Galabina Yordanova, David Yuan, Oana Stroe, Gemma Wood, Agata Laydon, Augustin Zídek, Tim Green, Kathryn Tunyasuvunakool, Stig Petersen, John Jumper, Ellen Clancy, Richard Green, Ankur Vora, Mira Lutfi, Michael Figurnov, Andrew Cowie, Nicole Hobbs, Pushmeet Kohli, Gerard J. Kleywegt, Ewan Birney, Demis Hassabis, Sameer Velankar:
AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. Nucleic Acids Res. 50(D1): 439-444 (2022) - [j39]Jonas Degrave, Federico Felici, Jonas Buchli, Michael Neunert, Brendan D. Tracey, Francesco Carpanese, Timo Ewalds, Roland Hafner, Abbas Abdolmaleki, Diego de Las Casas, Craig Donner, Leslie Fritz, Cristian Galperti, Andrea Huber, James Keeling, Maria Tsimpoukelli, Jackie Kay, Antoine Merle, Jean-Marc Moret, Seb Noury, Federico Pesamosca, David Pfau, Olivier Sauter, Cristian Sommariva, Stefano Coda, Basil Duval, Ambrogio Fasoli, Pushmeet Kohli, Koray Kavukcuoglu, Demis Hassabis, Martin A. Riedmiller:
Magnetic control of tokamak plasmas through deep reinforcement learning. Nat. 602(7897): 414-419 (2022) - [j38]Alhussein Fawzi, Matej Balog, Aja Huang, Thomas Hubert, Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Francisco J. R. Ruiz, Julian Schrittwieser, Grzegorz Swirszcz, David Silver, Demis Hassabis, Pushmeet Kohli:
Discovering faster matrix multiplication algorithms with reinforcement learning. Nat. 610(7930): 47-53 (2022) - [c180]Richard Evans, Matko Bosnjak, Lars Buesing, Kevin Ellis, David Pfau, Pushmeet Kohli, Marek J. Sergot:
Making Sense of Raw Input (Extended Abstract). IJCAI 2022: 5727-5731 - [i101]Yujia Li, David H. Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d'Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, Oriol Vinyals:
Competition-Level Code Generation with AlphaCode. CoRR abs/2203.07814 (2022) - 2021
- [j37]Vincent D. Blondel, Kyomin Jung, Pushmeet Kohli, Devavrat Shah, Seungpil Won:
Partition-Merge: Distributed Inference and Modularity Optimization. IEEE Access 9: 54032-54055 (2021) - [j36]Richard Evans, José Hernández-Orallo, Johannes Welbl, Pushmeet Kohli, Marek J. Sergot:
Making sense of sensory input. Artif. Intell. 293: 103438 (2021) - [j35]Richard Evans, Matko Bosnjak, Lars Buesing, Kevin Ellis, David P. Reichert, Pushmeet Kohli, Marek J. Sergot:
Making sense of raw input. Artif. Intell. 299: 103521 (2021) - [j34]Alex Davies, Petar Velickovic, Lars Buesing, Sam Blackwell, Daniel Zheng, Nenad Tomasev, Richard Tanburn, Peter W. Battaglia, Charles Blundell, András Juhász, Marc Lackenby, Geordie Williamson, Demis Hassabis, Pushmeet Kohli:
Advancing mathematics by guiding human intuition with AI. Nat. 600(7887): 70-74 (2021) - [c179]Johannes Welbl, Amelia Glaese, Jonathan Uesato, Sumanth Dathathri, John Mellor, Lisa Anne Hendricks, Kirsty Anderson, Pushmeet Kohli, Ben Coppin, Po-Sen Huang:
Challenges in Detoxifying Language Models. EMNLP (Findings) 2021: 2447-2469 - [c178]Sven Gowal, Po-Sen Huang, Aäron van den Oord, Timothy A. Mann, Pushmeet Kohli:
Self-supervised Adversarial Robustness for the Low-label, High-data Regime. ICLR 2021 - [i100]Alessandro De Palma, Rudy Bunel, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar:
Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition. CoRR abs/2104.06718 (2021) - [i99]Dan Rosenbaum, Marta Garnelo, Michal Zielinski, Charlie Beattie, Ellen Clancy, Andrea Huber, Pushmeet Kohli, Andrew W. Senior, John Jumper, Carl Doersch, S. M. Ali Eslami, Olaf Ronneberger, Jonas Adler:
Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs. CoRR abs/2106.14108 (2021) - [i98]Johannes Welbl, Amelia Glaese, Jonathan Uesato, Sumanth Dathathri, John Mellor, Lisa Anne Hendricks, Kirsty Anderson, Pushmeet Kohli, Ben Coppin, Po-Sen Huang:
Challenges in Detoxifying Language Models. CoRR abs/2109.07445 (2021) - 2020
- [j33]Rudy Bunel, Jingyue Lu, Ilker Turkaslan, Philip H. S. Torr, Pushmeet Kohli, M. Pawan Kumar:
Branch and Bound for Piecewise Linear Neural Network Verification. J. Mach. Learn. Res. 21: 42:1-42:39 (2020) - [j32]Andrew W. Senior, Richard Evans, John Jumper, James Kirkpatrick, Laurent Sifre, Tim Green, Chongli Qin, Augustin Zídek, Alexander W. R. Nelson, Alex Bridgland, Hugo Penedones, Stig Petersen, Karen Simonyan, Steve Crossan, Pushmeet Kohli, David T. Jones, David Silver, Koray Kavukcuoglu, Demis Hassabis:
Improved protein structure prediction using potentials from deep learning. Nat. 577(7792): 706-710 (2020) - [c177]Sven Gowal, Chongli Qin, Po-Sen Huang, A. Taylan Cemgil, Krishnamurthy Dvijotham, Timothy A. Mann, Pushmeet Kohli:
Achieving Robustness in the Wild via Adversarial Mixing With Disentangled Representations. CVPR 2020: 1208-1217 - [c176]Daniel Zoran, Mike Chrzanowski, Po-Sen Huang, Sven Gowal, Alex Mott, Pushmeet Kohli:
Towards Robust Image Classification Using Sequential Attention Models. CVPR 2020: 9480-9489 - [c175]Po-Sen Huang, Huan Zhang, Ray Jiang, Robert Stanforth, Johannes Welbl, Jack Rae, Vishal Maini, Dani Yogatama, Pushmeet Kohli:
Reducing Sentiment Bias in Language Models via Counterfactual Evaluation. EMNLP (Findings) 2020: 65-83 - [c174]A. Taylan Cemgil, Sumedh Ghaisas, Krishnamurthy (Dj) Dvijotham, Pushmeet Kohli:
Adversarially Robust Representations with Smooth Encoders. ICLR 2020 - [c173]Krishnamurthy (Dj) Dvijotham, Jamie Hayes, Borja Balle, J. Zico Kolter, Chongli Qin, András György, Kai Xiao, Sven Gowal, Pushmeet Kohli:
A Framework for robustness Certification of Smoothed Classifiers using F-Divergences. ICLR 2020 - [c172]Aditya Paliwal, Felix Gimeno, Vinod Nair, Yujia Li, Miles Lubin, Pushmeet Kohli, Oriol Vinyals:
Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs. ICLR 2020 - [c171]Johannes Welbl, Po-Sen Huang, Robert Stanforth, Sven Gowal, Krishnamurthy (Dj) Dvijotham, Martin Szummer, Pushmeet Kohli:
Towards Verified Robustness under Text Deletion Interventions. ICLR 2020 - [c170]Tsui-Wei Weng, Krishnamurthy (Dj) Dvijotham, Jonathan Uesato, Kai Xiao, Sven Gowal, Robert Stanforth, Pushmeet Kohli:
Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control. ICLR 2020 - [c169]Kexin Yi, Chuang Gan, Yunzhu Li, Pushmeet Kohli, Jiajun Wu, Antonio Torralba, Joshua B. Tenenbaum:
CLEVRER: Collision Events for Video Representation and Reasoning. ICLR 2020 - [c168]A. Taylan Cemgil, Sumedh Ghaisas, Krishnamurthy Dvijotham, Sven Gowal, Pushmeet Kohli:
The Autoencoding Variational Autoencoder. NeurIPS 2020 - [c167]Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin, Aditi Raghunathan, Jonathan Uesato, Rudy Bunel, Shreya Shankar, Jacob Steinhardt, Ian J. Goodfellow, Percy Liang, Pushmeet Kohli:
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming. NeurIPS 2020 - [c166]Chongli Qin, Yan Wu, Jost Tobias Springenberg, Andy Brock, Jeff Donahue, Timothy P. Lillicrap, Pushmeet Kohli:
Training Generative Adversarial Networks by Solving Ordinary Differential Equations. NeurIPS 2020 - [c165]Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar:
Lagrangian Decomposition for Neural Network Verification. UAI 2020: 370-379 - [i97]Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar:
Lagrangian Decomposition for Neural Network Verification. CoRR abs/2002.10410 (2020) - [i96]Yujia Li, Felix Gimeno, Pushmeet Kohli, Oriol Vinyals:
Strong Generalization and Efficiency in Neural Programs. CoRR abs/2007.03629 (2020) - [i95]Richard Evans, José Hernández-Orallo, Johannes Welbl, Pushmeet Kohli, Marek J. Sergot:
Evaluating the Apperception Engine. CoRR abs/2007.05367 (2020) - [i94]Jim Winkens, Rudy Bunel, Abhijit Guha Roy, Robert Stanforth, Vivek Natarajan, Joseph R. Ledsam, Patricia MacWilliams, Pushmeet Kohli, Alan Karthikesalingam, Simon Kohl, A. Taylan Cemgil, S. M. Ali Eslami, Olaf Ronneberger:
Contrastive Training for Improved Out-of-Distribution Detection. CoRR abs/2007.05566 (2020) - [i93]Sven Gowal, Chongli Qin, Jonathan Uesato, Timothy A. Mann, Pushmeet Kohli:
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples. CoRR abs/2010.03593 (2020) - [i92]Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin, Aditi Raghunathan, Jonathan Uesato, Rudy Bunel, Shreya Shankar, Jacob Steinhardt, Ian J. Goodfellow, Percy Liang, Pushmeet Kohli:
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming. CoRR abs/2010.11645 (2020) - [i91]Chongli Qin, Yan Wu, Jost Tobias Springenberg, Andrew Brock, Jeff Donahue, Timothy P. Lillicrap, Pushmeet Kohli:
Training Generative Adversarial Networks by Solving Ordinary Differential Equations. CoRR abs/2010.15040 (2020) - [i90]Jamie Hayes, Krishnamurthy Dvijotham, Yutian Chen, Sander Dieleman, Pushmeet Kohli, Norman Casagrande:
Towards transformation-resilient provenance detection of digital media. CoRR abs/2011.07355 (2020) - [i89]A. Taylan Cemgil, Sumedh Ghaisas, Krishnamurthy Dvijotham, Sven Gowal, Pushmeet Kohli:
Autoencoding Variational Autoencoder. CoRR abs/2012.03715 (2020) - [i88]Vinod Nair, Sergey Bartunov, Felix Gimeno, Ingrid von Glehn, Pawel Lichocki, Ivan Lobov, Brendan O'Donoghue, Nicolas Sonnerat, Christian Tjandraatmadja, Pengming Wang, Ravichandra Addanki, Tharindi Hapuarachchi, Thomas Keck, James Keeling, Pushmeet Kohli, Ira Ktena, Yujia Li, Oriol Vinyals, Yori Zwols:
Solving Mixed Integer Programs Using Neural Networks. CoRR abs/2012.13349 (2020)
2010 – 2019
- 2019
- [j31]Danhang Tang, Qi Ye, Shanxin Yuan, Jonathan Taylor, Pushmeet Kohli, Cem Keskin, Tae-Kyun Kim, Jamie Shotton:
Opening the Black Box: Hierarchical Sampling Optimization for Hand Pose Estimation. IEEE Trans. Pattern Anal. Mach. Intell. 41(9): 2161-2175 (2019) - [j30]Thomas Joy, Alban Desmaison, Thalaiyasingam Ajanthan, Rudy Bunel, Mathieu Salzmann, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar:
Efficient Relaxations for Dense CRFs with Sparse Higher-Order Potentials. SIAM J. Imaging Sci. 12(1): 287-318 (2019) - [c164]Ray Jiang, Silvia Chiappa, Tor Lattimore, András György, Pushmeet Kohli:
Degenerate Feedback Loops in Recommender Systems. AIES 2019: 383-390 - [c163]Dylan Banarse, Yoram Bachrach, Siqi Liu, Guy Lever, Nicolas Heess, Chrisantha Fernando, Pushmeet Kohli, Thore Graepel:
The Body is Not a Given: Joint Agent Policy Learning and Morphology Evolution. AAMAS 2019: 1134-1142 - [c162]Chenglong Wang, Rudy Bunel, Krishnamurthy Dvijotham, Po-Sen Huang, Edward Grefenstette, Pushmeet Kohli:
Knowing When to Stop: Evaluation and Verification of Conformity to Output-Size Specifications. CVPR 2019: 12260-12269 - [c161]Po-Sen Huang, Robert Stanforth, Johannes Welbl, Chris Dyer, Dani Yogatama, Sven Gowal, Krishnamurthy Dvijotham, Pushmeet Kohli:
Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation. EMNLP/IJCNLP (1) 2019: 4081-4091 - [c160]Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Chongli Qin, Jonathan Uesato, Relja Arandjelovic, Timothy Arthur Mann, Pushmeet Kohli:
Scalable Verified Training for Provably Robust Image Classification. ICCV 2019: 4841-4850 - [c159]Dzmitry Bahdanau, Felix Hill, Jan Leike, Edward Hughes, Seyed Arian Hosseini, Pushmeet Kohli, Edward Grefenstette:
Learning to Understand Goal Specifications by Modelling Reward. ICLR (Poster) 2019 - [c158]Jiayuan Mao, Chuang Gan, Pushmeet Kohli, Joshua B. Tenenbaum, Jiajun Wu:
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision. ICLR 2019 - [c157]Nantas Nardelli, Gabriel Synnaeve, Zeming Lin, Pushmeet Kohli, Philip H. S. Torr, Nicolas Usunier:
Value Propagation Networks. ICLR (Poster) 2019 - [c156]Chongli Qin, Krishnamurthy (Dj) Dvijotham, Brendan O'Donoghue, Rudy Bunel, Robert Stanforth, Sven Gowal, Jonathan Uesato, Grzegorz Swirszcz, Pushmeet Kohli:
Verification of Non-Linear Specifications for Neural Networks. ICLR (Poster) 2019 - [c155]David Saxton, Edward Grefenstette, Felix Hill, Pushmeet Kohli:
Analysing Mathematical Reasoning Abilities of Neural Models. ICLR (Poster) 2019 - [c154]Jonathan Uesato, Ananya Kumar, Csaba Szepesvári, Tom Erez, Avraham Ruderman, Keith Anderson, Krishnamurthy (Dj) Dvijotham, Nicolas Heess, Pushmeet Kohli:
Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures. ICLR (Poster) 2019 - [c153]Victor Bapst, Alvaro Sanchez-Gonzalez, Carl Doersch, Kimberly L. Stachenfeld, Pushmeet Kohli, Peter W. Battaglia, Jessica B. Hamrick:
Structured agents for physical construction. ICML 2019: 464-474 - [c152]Thomas Kipf, Yujia Li, Hanjun Dai, Vinícius Flores Zambaldi, Alvaro Sanchez-Gonzalez, Edward Grefenstette, Pushmeet Kohli, Peter W. Battaglia:
CompILE: Compositional Imitation Learning and Execution. ICML 2019: 3418-3428 - [c151]Yujia Li, Chenjie Gu, Thomas Dullien, Oriol Vinyals, Pushmeet Kohli:
Graph Matching Networks for Learning the Similarity of Graph Structured Objects. ICML 2019: 3835-3845 - [c150]Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Timothy A. Mann, Pushmeet Kohli:
A Dual Approach to Verify and Train Deep Networks. IJCAI 2019: 6156-6160 - [c149]Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli:
Learning Transferable Graph Exploration. NeurIPS 2019: 2514-2525 - [c148]Jean-Baptiste Alayrac, Jonathan Uesato, Po-Sen Huang, Alhussein Fawzi, Robert Stanforth, Pushmeet Kohli:
Are Labels Required for Improving Adversarial Robustness? NeurIPS 2019: 12192-12202 - [c147]Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli:
Adversarial Robustness through Local Linearization. NeurIPS 2019: 13824-13833 - [c146]Krishnamurthy (Dj) Dvijotham, Robert Stanforth, Sven Gowal, Chongli Qin, Soham De, Pushmeet Kohli:
Efficient Neural Network Verification with Exactness Characterization. UAI 2019: 497-507 - [i87]Chongli Qin, Krishnamurthy (Dj) Dvijotham, Brendan O'Donoghue, Rudy Bunel, Robert Stanforth, Sven Gowal, Jonathan Uesato, Grzegorz Swirszcz, Pushmeet Kohli:
Verification of Non-Linear Specifications for Neural Networks. CoRR abs/1902.09592 (2019) - [i86]Ray Jiang, Silvia Chiappa, Tor Lattimore, András György, Pushmeet Kohli:
Degenerate Feedback Loops in Recommender Systems. CoRR abs/1902.10730 (2019) - [i85]Alexandre Galashov, Jonathan Schwarz, Hyunjik Kim, Marta Garnelo, David Saxton, Pushmeet Kohli, S. M. Ali Eslami, Yee Whye Teh:
Meta-Learning surrogate models for sequential decision making. CoRR abs/1903.11907 (2019) - [i84]David Saxton, Edward Grefenstette, Felix Hill, Pushmeet Kohli:
Analysing Mathematical Reasoning Abilities of Neural Models. CoRR abs/1904.01557 (2019) - [i83]Victor Bapst, Alvaro Sanchez-Gonzalez, Carl Doersch, Kimberly L. Stachenfeld, Pushmeet Kohli, Peter W. Battaglia, Jessica B. Hamrick:
Structured agents for physical construction. CoRR abs/1904.03177 (2019) - [i82]Chenglong Wang, Rudy Bunel, Krishnamurthy Dvijotham, Po-Sen Huang, Edward Grefenstette, Pushmeet Kohli:
Knowing When to Stop: Evaluation and Verification of Conformity to Output-size Specifications. CoRR abs/1904.12004 (2019) - [i81]Jiayuan Mao, Chuang Gan, Pushmeet Kohli, Joshua B. Tenenbaum, Jiajun Wu:
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision. CoRR abs/1904.12584 (2019) - [i80]Yujia Li, Chenjie Gu, Thomas Dullien, Oriol Vinyals, Pushmeet Kohli:
Graph Matching Networks for Learning the Similarity of Graph Structured Objects. CoRR abs/1904.12787 (2019) - [i79]Aditya Paliwal, Felix Gimeno, Vinod Nair, Yujia Li, Miles Lubin, Pushmeet Kohli, Oriol Vinyals:
REGAL: Transfer Learning For Fast Optimization of Computation Graphs. CoRR abs/1905.02494 (2019) - [i78]Simon A. A. Kohl, Bernardino Romera-Paredes, Klaus H. Maier-Hein, Danilo Jimenez Rezende, S. M. Ali Eslami, Pushmeet Kohli, Andrew Zisserman, Olaf Ronneberger:
A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities. CoRR abs/1905.13077 (2019) - [i77]Jonathan Uesato, Jean-Baptiste Alayrac, Po-Sen Huang, Robert Stanforth, Alhussein Fawzi, Pushmeet Kohli:
Are Labels Required for Improving Adversarial Robustness? CoRR abs/1905.13725 (2019) - [i76]Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli:
Adversarial Robustness through Local Linearization. CoRR abs/1907.02610 (2019) - [i75]Po-Sen Huang, Robert Stanforth, Johannes Welbl, Chris Dyer, Dani Yogatama, Sven Gowal, Krishnamurthy Dvijotham, Pushmeet Kohli:
Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation. CoRR abs/1909.01492 (2019) - [i74]Rudy Bunel, Jingyue Lu, Ilker Turkaslan, Philip H. S. Torr, Pushmeet Kohli, M. Pawan Kumar:
Branch and Bound for Piecewise Linear Neural Network Verification. CoRR abs/1909.06588 (2019) - [i73]Kexin Yi, Chuang Gan, Yunzhu Li, Pushmeet Kohli, Jiajun Wu, Antonio Torralba, Joshua B. Tenenbaum:
CLEVRER: CoLlision Events for Video REpresentation and Reasoning. CoRR abs/1910.01442 (2019) - [i72]Richard Evans, José Hernández-Orallo, Johannes Welbl, Pushmeet Kohli, Marek J. Sergot:
Making sense of sensory input. CoRR abs/1910.02227 (2019) - [i71]Sven Gowal, Jonathan Uesato, Chongli Qin, Po-Sen Huang, Timothy A. Mann, Pushmeet Kohli:
An Alternative Surrogate Loss for PGD-based Adversarial Testing. CoRR abs/1910.09338 (2019) - [i70]Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli:
Learning Transferable Graph Exploration. CoRR abs/1910.12980 (2019) - [i69]Po-Sen Huang, Huan Zhang, Ray Jiang, Robert Stanforth, Johannes Welbl, Jack Rae, Vishal Maini, Dani Yogatama, Pushmeet Kohli:
Reducing Sentiment Bias in Language Models via Counterfactual Evaluation. CoRR abs/1911.03064 (2019) - [i68]Daniel Zoran, Mike Chrzanowski, Po-Sen Huang, Sven Gowal, Alex Mott, Pushmeet Kohli:
Towards Robust Image Classification Using Sequential Attention Models. CoRR abs/1912.02184 (2019) - [i67]Sven Gowal, Chongli Qin, Po-Sen Huang, A. Taylan Cemgil, Krishnamurthy Dvijotham, Timothy A. Mann, Pushmeet Kohli:
Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations. CoRR abs/1912.03192 (2019) - 2018
- [c145]Zi Wang, Clement Gehring, Pushmeet Kohli, Stefanie Jegelka:
Batched Large-scale Bayesian Optimization in High-dimensional Spaces. AISTATS 2018: 745-754 - [c144]Dzmitry Bahdanau, Felix Hill, Jan Leike, Edward Hughes, Pushmeet Kohli, Edward Grefenstette:
Jointly Learning "What" and "How" from Instructions and Goal-States. ICLR (Workshop) 2018 - [c143]Rudy Bunel, Matthew J. Hausknecht, Jacob Devlin, Rishabh Singh, Pushmeet Kohli:
Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis. ICLR (Poster) 2018 - [c142]Richard Evans, David Saxton, David Amos, Pushmeet Kohli, Edward Grefenstette:
Can Neural Networks Understand Logical Entailment? ICLR (Poster) 2018 - [c141]Jonathan Uesato, Brendan O'Donoghue, Pushmeet Kohli, Aäron van den Oord:
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks. ICML 2018: 5032-5041 - [c140]Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri:
Programmatically Interpretable Reinforcement Learning. ICML 2018: 5052-5061 - [c139]Sahil Bhatia, Pushmeet Kohli, Rishabh Singh:
Neuro-symbolic program corrector for introductory programming assignments. ICSE 2018: 60-70 - [c138]Kexin Yi, Jiajun Wu, Chuang Gan, Antonio Torralba, Pushmeet Kohli, Josh Tenenbaum:
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding. NeurIPS 2018: 1039-1050 - [c137]Rudy Bunel, Ilker Turkaslan, Philip H. S. Torr, Pushmeet Kohli, Pawan Kumar Mudigonda:
A Unified View of Piecewise Linear Neural Network Verification. NeurIPS 2018: 4795-4804 - [c136]Krishnamurthy Dvijotham, Robert Stanforth, Sven Gowal, Timothy A. Mann, Pushmeet Kohli:
A Dual Approach to Scalable Verification of Deep Networks. UAI 2018: 550-559 - [i66]Jonathan Uesato, Brendan O'Donoghue, Aäron van den Oord, Pushmeet Kohli:
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks. CoRR abs/1802.05666 (2018) - [i65]Richard Evans, David Saxton, David Amos, Pushmeet Kohli, Edward Grefenstette:
Can Neural Networks Understand Logical Entailment? CoRR abs/1802.08535 (2018) - [i64]Krishnamurthy Dvijotham, Robert Stanforth, Sven Gowal, Timothy A. Mann, Pushmeet Kohli:
A Dual Approach to Scalable Verification of Deep Networks. CoRR abs/1803.06567 (2018) - [i63]Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri:
Programmatically Interpretable Reinforcement Learning. CoRR abs/1804.02477 (2018) - [i62]Rudy Bunel, Matthew J. Hausknecht, Jacob Devlin, Rishabh Singh, Pushmeet Kohli:
Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis. CoRR abs/1805.04276 (2018) - [i61]Thomas Joy, Alban Desmaison, Thalaiyasingam Ajanthan, Rudy Bunel, Mathieu Salzmann, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar:
Efficient Relaxations for Dense CRFs with Sparse Higher Order Potentials. CoRR abs/1805.09028 (2018) - [i60]