Bradley Gram-Hansen

According to our database, Bradley Gram-Hansen authored at least 13 papers between 2018 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Amortized Rejection Sampling in Universal Probabilistic Programming.

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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Extending probabilistic programming systems and applying them to real-world simulators.

Bradley Gram-Hansen

PhD thesis, 2021

2020

Simulation-Based Inference for Global Health Decisions.

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

CoRR, 2020

2019

Hijacking Malaria Simulators with Probabilistic Programming.

Bradley Gram-Hansen, Christian Schröder de Witt, Tom Rainforth, Philip H. S. Torr, Yee Whye Teh, Atilim Günes Baydin

CoRR, 2019

Etalumis: bringing probabilistic programming to scientific simulators at scale.

Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood

Proceedings of the International Conference for High Performance Computing, 2019

Usability of Probabilistic Programming Languages.

Alan F. Blackwell, Luke Church, Martin Erwig, James Geddes, Andy Gordon, Maria I. Gorinova, Atilim Gunes Baydin, Bradley Gram-Hansen, Tobias Kohn, Neil Lawrence, Vikash Mansinghka, Brooks Paige, Tomas Petricek, Diana Robinson, Advait Sarkar, Oliver Strickson

Proceedings of the 30th Annual Workshop of the Psychology of Programming Interest Group, 2019

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model.

Atilim Gunes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Saeid Naderiparizi, Andreas Munk, Jialin Liu, Bradley Gram-Hansen, Gilles Louppe, Lawrence Meadows, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models.

Yuan Zhou, Bradley J. Gram-Hansen, Tobias Kohn, Tom Rainforth, Hongseok Yang, Frank Wood

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Mapping Informal Settlements in Developing Countries using Machine Learning and Low Resolution Multi-spectral Data.

Bradley J. Gram-Hansen, Patrick Helber, Indhu Varatharajan, Faiza Azam, Alejandro Coca-Castro, Veronika Kopacková, Piotr Bilinski

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018

Mapping Informal Settlements in Developing Countries with Multi-resolution, Multi-spectral Data.

Patrick Helber, Bradley Gram-Hansen, Indhu Varatharajan, Faiza Azam, Alejandro Coca-Castro, Veronika Kopacková, Piotr Bilinski

CoRR, 2018

Generating Material Maps to Map Informal Settlements.

Patrick Helber, Bradley Gram-Hansen, Indhu Varatharajan, Faiza Azam, Alejandro Coca-Castro, Veronika Kopacková, Piotr Bilinski

CoRR, 2018

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model.

Atilim Gunes Baydin, Lukas Heinrich, Wahid Bhimji, Bradley Gram-Hansen, Gilles Louppe, Lei Shao, Prabhat, Kyle Cranmer, Frank D. Wood

CoRR, 2018

Discontinuous Hamiltonian Monte Carlo for Probabilistic Programs.

Bradley Gram-Hansen, Yuan Zhou, Tobias Kohn, Hongseok Yang, Frank D. Wood

CoRR, 2018