| Relational inductive biases, deep learning, and graph networks PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ... arXiv preprint arXiv:1806.01261, 2018 | 3102 | 2018 |
| Sample efficient actor-critic with experience replay Z Wang, V Bapst, N Heess, V Mnih, R Munos, K Kavukcuoglu, ... arXiv preprint arXiv:1611.01224, 2016 | 910 | 2016 |
| Distral: Robust multitask reinforcement learning Y Teh, V Bapst, WM Czarnecki, J Quan, J Kirkpatrick, R Hadsell, N Heess, ... Advances in neural information processing systems 30, 2017 | 553 | 2017 |
| Unveiling the predictive power of static structure in glassy systems V Bapst, T Keck, A Grabska-Barwińska, C Donner, ED Cubuk, ... Nature Physics 16 (4), 448-454, 2020 | 266 | 2020 |
| Relational deep reinforcement learning V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ... arXiv preprint arXiv:1806.01830, 2018 | 252 | 2018 |
| Hyperbolic attention networks C Gulcehre, M Denil, M Malinowski, A Razavi, R Pascanu, KM Hermann, ... arXiv preprint arXiv:1805.09786, 2018 | 240 | 2018 |
| Deep reinforcement learning with relational inductive biases V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ... International conference on learning representations, 2018 | 197 | 2018 |
| The quantum adiabatic algorithm applied to random optimization problems: The quantum spin glass perspective V Bapst, L Foini, F Krzakala, G Semerjian, F Zamponi Physics Reports 523 (3), 127-205, 2013 | 167 | 2013 |
| Relational inductive biases, deep learning, and graph networks. arXiv 2018 PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ... arXiv preprint arXiv:1806.01261, 2018 | 159 | 2018 |
| Hamiltonian graph networks with ode integrators A Sanchez-Gonzalez, V Bapst, K Cranmer, P Battaglia arXiv preprint arXiv:1909.12790, 2019 | 139 | 2019 |
| Relational inductive bias for physical construction in humans and machines JB Hamrick, KR Allen, V Bapst, T Zhu, KR McKee, JB Tenenbaum, ... arXiv preprint arXiv:1806.01203, 2018 | 113 | 2018 |
| Structured agents for physical construction V Bapst, A Sanchez-Gonzalez, C Doersch, K Stachenfeld, P Kohli, ... International conference on machine learning, 464-474, 2019 | 96 | 2019 |
| Anomalous Softening of Crystals X Rojas, A Haziot, V Bapst, S Balibar, HJ Maris Physical Review Letters 105 (14), 145302, 2010 | 90 | 2010 |
| On quantum mean-field models and their quantum annealing V Bapst, G Semerjian Journal of Statistical Mechanics: Theory and Experiment 2012 (06), P06007, 2012 | 75 | 2012 |
| Relational inductive biases, deep learning, and graph networks (2018) PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ... arXiv preprint arXiv:1806.01261, 1806 | 68 | 1806 |
| Generating interpretable images with controllable structure S Reed, A van den Oord, N Kalchbrenner, V Bapst, M Botvinick, ... | 63 | 2016 |
| The condensation phase transition in random graph coloring V Bapst, A Coja-Oghlan, S Hetterich, F Raßmann, D Vilenchik Communications in Mathematical Physics 341, 543-606, 2016 | 62 | 2016 |
| Combining q-learning and search with amortized value estimates JB Hamrick, V Bapst, A Sanchez-Gonzalez, T Pfaff, T Weber, L Buesing, ... arXiv preprint arXiv:1912.02807, 2019 | 50 | 2019 |
| Harnessing the Bethe free energy V Bapst, A Coja‐Oghlan Random structures & algorithms 49 (4), 694-741, 2016 | 36 | 2016 |
| The large connectivity limit of the Anderson model on tree graphs V Bapst Journal of Mathematical Physics 55 (9), 2014 | 27 | 2014 |
Peter BattagliaResearch Scientist, DeepMindVerified email at google.com
