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Daniel Selsam
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2020 – today
- 2024
- [i12]Aaron Jaech, Adam Kalai, Adam Lerer, Adam Richardson, Ahmed El-Kishky, Aiden Low, Alec Helyar, Aleksander Madry, Alex Beutel, Alex Carney, Alex Iftimie, Alex Karpenko, Alex Tachard Passos, Alexander Neitz, Alexander Prokofiev, Alexander Wei, Allison Tam, Ally Bennett, Ananya Kumar, Andre Saraiva, Andrea Vallone, Andrew Duberstein, Andrew Kondrich, Andrey Mishchenko, Andy Applebaum, Angela Jiang, Ashvin Nair, Barret Zoph, Behrooz Ghorbani, Ben Rossen, Benjamin Sokolowsky, Boaz Barak, Bob McGrew, Borys Minaiev, Botao Hao, Bowen Baker, Brandon Houghton, Brandon McKinzie, Brydon Eastman, Camillo Lugaresi, Cary Bassin, Cary Hudson, Chak Ming Li, Charles de Bourcy, Chelsea Voss, Chen Shen, Chong Zhang, Chris Koch, Chris Orsinger, Christopher Hesse, Claudia Fischer, Clive Chan, Dan Roberts, Daniel Kappler, Daniel Levy, Daniel Selsam, David Dohan, David Farhi, David Mely, David Robinson, Dimitris Tsipras, Doug Li, Dragos Oprica, Eben Freeman, Eddie Zhang, Edmund Wong, Elizabeth Proehl, Enoch Cheung, Eric Mitchell, Eric Wallace, Erik Ritter, Evan Mays, Fan Wang, Felipe Petroski Such, Filippo Raso, Florencia Leoni, Foivos Tsimpourlas, Francis Song, Fred von Lohmann, Freddie Sulit, Geoff Salmon, Giambattista Parascandolo, Gildas Chabot, Grace Zhao, Greg Brockman, Guillaume Leclerc, Hadi Salman, Haiming Bao, Hao Sheng, Hart Andrin, Hessam Bagherinezhad, Hongyu Ren, Hunter Lightman, Hyung Won Chung, Ian Kivlichan, Ian O'Connell, Ian Osband, Ignasi Clavera Gilaberte, Ilge Akkaya:
OpenAI o1 System Card. CoRR abs/2412.16720 (2024) - 2021
- [c6]Ryan Krueger
, Jesse Michael Han, Daniel Selsam:
Automatically Building Diagrams for Olympiad Geometry Problems. CADE 2021: 577-588 - [i11]Daniel Selsam, Jesse Michael Han:
k-Equivalence Relations and Associated Algorithms. CoRR abs/2102.04633 (2021) - 2020
- [j1]Daniel Selsam, Simon Hudon, Leonardo de Moura:
Sealing pointer-based optimizations behind pure functions. Proc. ACM Program. Lang. 4(ICFP): 115:1-115:20 (2020) - [i10]Daniel Selsam, Sebastian Ullrich, Leonardo de Moura:
Tabled Typeclass Resolution. CoRR abs/2001.04301 (2020) - [i9]Daniel Selsam, Simon Hudon, Leonardo de Moura:
Sealing Pointer-Based Optimizations Behind Pure Functions. CoRR abs/2003.01685 (2020) - [i8]Ryan Krueger, Jesse Michael Han, Daniel Selsam:
Automatically Building Diagrams for Olympiad Geometry Problems. CoRR abs/2012.02590 (2020) - [i7]Daniel Selsam, Jesse Michael Han, Leonardo de Moura, Patrice Godefroid:
Universal Policies for Software-Defined MDPs. CoRR abs/2012.11401 (2020)
2010 – 2019
- 2019
- [b1]Daniel Selsam:
Neural networks and the satisfiability problem. Stanford University, USA, 2019 - [c5]Daniel Selsam, Matthew Lamm, Benedikt Bünz, Percy Liang, Leonardo de Moura, David L. Dill:
Learning a SAT Solver from Single-Bit Supervision. ICLR (Poster) 2019 - [c4]Daniel Selsam, Nikolaj S. Bjørner:
Guiding High-Performance SAT Solvers with Unsat-Core Predictions. SAT 2019: 336-353 - [i6]Daniel Selsam, Nikolaj S. Bjørner:
NeuroCore: Guiding High-Performance SAT Solvers with Unsat-Core Predictions. CoRR abs/1903.04671 (2019) - 2018
- [i5]Daniel Selsam, Matthew Lamm, Benedikt Bünz, Percy Liang, Leonardo de Moura, David L. Dill:
Learning a SAT Solver from Single-Bit Supervision. CoRR abs/1802.03685 (2018) - 2017
- [c3]Daniel Selsam, Percy Liang, David L. Dill:
Developing Bug-Free Machine Learning Systems With Formal Mathematics. ICML 2017: 3047-3056 - [i4]Daniel Selsam, Leonardo de Moura:
Congruence Closure in Intensional Type Theory. CoRR abs/1701.04391 (2017) - [i3]Daniel Selsam, Percy Liang, David L. Dill:
Developing Bug-Free Machine Learning Systems With Formal Mathematics. CoRR abs/1706.08605 (2017) - 2016
- [c2]Daniel Selsam, Leonardo de Moura:
Congruence Closure in Intensional Type Theory. IJCAR 2016: 99-115 - [c1]Alexander J. Ratner, Christopher De Sa, Sen Wu, Daniel Selsam, Christopher Ré:
Data Programming: Creating Large Training Sets, Quickly. NIPS 2016: 3567-3575 - [i2]Alexander Ratner, Christopher De Sa, Sen Wu, Daniel Selsam, Christopher Ré:
Data Programming: Creating Large Training Sets, Quickly. CoRR abs/1605.07723 (2016) - 2014
- [i1]Vikash Mansinghka, Daniel Selsam, Yura N. Perov:
Venture: a higher-order probabilistic programming platform with programmable inference. CoRR abs/1404.0099 (2014)
Coauthor Index
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