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2020 – today
- 2024
[i7]David Brandfonbrener, Sibi Raja, Tarun Prasad, Chloe Loughridge, Jianang Yang, Simon Henniger, William E. Byrd, Robert Zinkov, Nada Amin
:
Verified Multi-Step Synthesis using Large Language Models and Monte Carlo Tree Search. CoRR abs/2402.08147 (2024)- [i6]Alberto Cabezas, Adrien Corenflos, Junpeng Lao, Rémi Louf, Antoine Carnec, Kaustubh Chaudhari, Reuben Cohn-Gordon, Jeremie Coullon, Wei Deng, Sam Duffield, Gerardo Duràn-Martín, Marcin Elantkowski, Dan Foreman-Mackey, Michele Gregori, Carlos Iguaran, Ravin Kumar, Martin Lysy, Kevin Murphy, Juan Camilo Orduz, Karm Patel, Xi Wang, Rob Zinkov:
BlackJAX: Composable Bayesian inference in JAX. CoRR abs/2402.10797 (2024) - 2023
- [j1]Oriol Abril Pla, Virgile Andréani, Colin Carroll, Larry Dong, Christopher Fonnesbeck, Maxim Kochurov, Ravin Kumar, Junpeng Lao, Christian C. Luhmann, Osvaldo A. Martin, Michael Osthege, Ricardo Vieira, Thomas V. Wiecki, Robert Zinkov:
PyMC: a modern, and comprehensive probabilistic programming framework in Python. PeerJ Comput. Sci. 9: e1516 (2023) - 2022
- [c9]Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Gunes Baydin, Bradley J. Gram-Hansen, Christian A. Schröder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood:
Amortized Rejection Sampling in Universal Probabilistic Programming. AISTATS 2022: 8392-8412 - 2021
- [c8]Robert Zinkov, William E. Byrd:
probKanren: A Simple Probabilistic Extension for microKanren. ICLP Workshops 2021 - 2020
- [i5]Christian Schröder de Witt, Bradley Gram-Hansen, Nantas Nardelli, Andrew Gambardella, Robert Zinkov, Puneet K. Dokania, N. Siddharth, Ana Belen Espinosa-Gonzalez, Ara Darzi, Philip H. S. Torr, Atilim Günes Baydin:
Simulation-Based Inference for Global Health Decisions. CoRR abs/2005.07062 (2020)
2010 – 2019
- 2019
- [i4]Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Günes Baydin, Bradley Gram-Hansen, Christian Schröder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood:
Amortized Rejection Sampling in Universal Probabilistic Programming. CoRR abs/1910.09056 (2019) - 2018
- [c7]Fatemeh Torabi Asr, Robert Zinkov, Michael N. Jones:
Querying Word Embeddings for Similarity and Relatedness. NAACL-HLT 2018: 675-684 - [c6]Stefan Webb, Adam Golinski, Robert Zinkov, Siddharth Narayanaswamy, Tom Rainforth, Yee Whye Teh, Frank Wood:
Faithful Inversion of Generative Models for Effective Amortized Inference. NeurIPS 2018: 3074-3084 - 2017
- [c5]Tuan Anh Le, Atilim Günes Baydin, Robert Zinkov, Frank D. Wood:
Using synthetic data to train neural networks is model-based reasoning. IJCNN 2017: 3514-3521 - [c4]Robert Zinkov, Chung-chieh Shan:
Composing Inference Algorithms as Program Transformations. UAI 2017 - [i3]Tuan Anh Le, Atilim Gunes Baydin, Robert Zinkov, Frank D. Wood:
Using Synthetic Data to Train Neural Networks is Model-Based Reasoning. CoRR abs/1703.00868 (2017) - [i2]Stefan Webb, Adam Golinski, Robert Zinkov, N. Siddharth, Yee Whye Teh, Frank D. Wood:
Faithful Model Inversion Substantially Improves Auto-encoding Variational Inference. CoRR abs/1712.00287 (2017) - 2016
- [c3]Praveen Narayanan, Jacques Carette, Wren Romano, Chung-chieh Shan, Robert Zinkov:
Probabilistic Inference by Program Transformation in Hakaru (System Description). FLOPS 2016: 62-79 - [i1]Robert Zinkov, Chung-chieh Shan:
Composing inference algorithms as program transformations. CoRR abs/1603.01882 (2016)
2000 – 2009
- 2009
- [c2]Emma Bowring, Zhengyu Yin, Rob Zinkov, Milind Tambe:
Sensitivity analysis for distributed optimization with resource constraints. AAMAS (1) 2009: 633-640 - 2008
- [c1]John Asmuth, Michael L. Littman, Robert Zinkov:
Potential-based Shaping in Model-based Reinforcement Learning. AAAI 2008: 604-609
Coauthor Index
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last updated on 2024-10-07 21:23 CEST by the dblp team
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