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2020 – today
- 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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