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Robert Zinkov
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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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