The Quantum Adiabatic Algorithm applied to random optimization problems: the quantum spin glass perspective - Victor Bapst; Laura Foini; Florent Krzakala; Guilhem Semerjian; Francesco Zamponi (CoRR, 2012)

The effect of quantum fluctuations on the coloring of random graphs - Victor Bapst; Guilhem Semerjian; Francesco Zamponi (CoRR, 2013)

The Condensation Phase Transition in Random Graph Coloring. - Victor Bapst; Amin Coja-Oghlan; Samuel Hetterich; Felicia Raßmann; Dan Vilenchik (APPROX-RANDOM, 2014)

A positive temperature phase transition in random hypergraph 2-coloring. - Victor Bapst; Amin Coja-Oghlan; Felicia Raßmann (CoRR, 2014)

The Condensation Phase Transition in the Regular k-SAT Model. - Victor Bapst; Amin Coja-Oghlan (APPROX-RANDOM, 2016)

Harnessing the Bethe free energy. - Victor Bapst; Amin Coja-Oghlan (Random Struct. Algorithms, 2016)

Sample Efficient Actor-Critic with Experience Replay. - Ziyu Wang 001; Victor Bapst; Nicolas Heess; Volodymyr Mnih; Rémi Munos; Koray Kavukcuoglu; Nando de Freitas (ICLR (Poster), 2017)

Distral: Robust multitask reinforcement learning. - Yee Whye Teh; Victor Bapst; Wojciech M. Czarnecki; John Quan; James Kirkpatrick; Raia Hadsell; Nicolas Heess; Razvan Pascanu (NIPS, 2017)

Planting Colourings Silently. - Victor Bapst; Amin Coja-Oghlan; Charilaos Efthymiou 001 (Comb. Probab. Comput., 2017)

Relational inductive bias for physical construction in humans and machines. - Jessica B. Hamrick; Kelsey R. Allen; Victor Bapst; Tina Zhu; Kevin R. McKee; Josh Tenenbaum 001; Peter W. Battaglia (CogSci, 2018)

Relational inductive biases, deep learning, and graph networks. - Peter W. Battaglia; Jessica B. Hamrick; Victor Bapst; Alvaro Sanchez-Gonzalez; Vinícius Flores Zambaldi; Mateusz Malinowski; Andrea Tacchetti; David Raposo; Adam Santoro; Ryan Faulkner 001; Çaglar Gülçehre; H. Francis Song; et al. (CoRR, 2018)

Relational Deep Reinforcement Learning. - Vinícius Flores Zambaldi; David Raposo; Adam Santoro; Victor Bapst; Yujia Li 001; Igor Babuschkin; Karl Tuyls; David P. Reichert; Timothy P. Lillicrap; Edward Lockhart; Murray Shanahan; Victoria Langston; et al. (CoRR, 2018)

Hyperbolic Attention Networks. - Çaglar Gülçehre; Misha Denil; Mateusz Malinowski; Ali Razavi; Razvan Pascanu; Karl Moritz Hermann; Peter W. Battaglia; Victor Bapst; David Raposo; Adam Santoro; Nando de Freitas (ICLR (Poster), 2019)

Deep reinforcement learning with relational inductive biases. - Vinícius Flores Zambaldi; David Raposo; Adam Santoro; Victor Bapst; Yujia Li 001; Igor Babuschkin; Karl Tuyls; David P. Reichert; Timothy P. Lillicrap; Edward Lockhart; Murray Shanahan; Victoria Langston; et al. (ICLR (Poster), 2019)

Structured agents for physical construction. - Victor Bapst; Alvaro Sanchez-Gonzalez; Carl Doersch; Kimberly L. Stachenfeld; Pushmeet Kohli; Peter W. Battaglia; Jessica B. Hamrick (ICML, 2019)

Hamiltonian Graph Networks with ODE Integrators. - Alvaro Sanchez-Gonzalez; Victor Bapst; Kyle Cranmer; Peter W. Battaglia (CoRR, 2019)

Object-oriented state editing for HRL. - Victor Bapst; Alvaro Sanchez-Gonzalez; Omar Shams; Kimberly L. Stachenfeld; Peter W. Battaglia; Satinder Singh 001; Jessica B. Hamrick (CoRR, 2019)

Combining Q-Learning and Search with Amortized Value Estimates. - Jessica B. Hamrick; Victor Bapst; Alvaro Sanchez-Gonzalez; Tobias Pfaff; Theophane Weber; Lars Buesing; Peter W. Battaglia (ICLR, 2020)

A Deep Learning Approach for Characterizing Major Galaxy Mergers. - Skanda Koppula; Victor Bapst; Marc Huertas-Company; Sam Blackwell; Agnieszka Grabska-Barwinska; Sander Dieleman; Andrea Huber; Natasha Antropova; Mikolaj Binkowski; Hannah Openshaw; Adrià Recasens; Fernando Caro; et al. (CoRR, 2021)