Follow
Christian Weilbach
Title
Cited by
Cited by
Year
Flexible diffusion modeling of long videos
W Harvey, S Naderiparizi, V Masrani, C Weilbach, F Wood
Advances in Neural Information Processing Systems 35, 27953-27965, 2022
1502022
Structured conditional continuous normalizing flows for efficient amortized inference in graphical models
C Weilbach, B Beronov, F Wood, W Harvey
International Conference on Artificial Intelligence and Statistics, 4441-4451, 2020
192020
Planning as inference in epidemiological dynamics models
F Wood, A Warrington, S Naderiparizi, C Weilbach, V Masrani, W Harvey, ...
Frontiers in Artificial Intelligence 4, 550603, 2022
172022
Inferring the structure of ordinary differential equations
J Weilbach, S Gerwinn, C Weilbach, M Kandemir
arXiv preprint arXiv:2107.07345, 2021
42021
Graphically structured diffusion models
CD Weilbach, W Harvey, F Wood
International Conference on Machine Learning, 36887-36909, 2023
32023
Efficient inference amortization in graphical models using structured continuous conditional normalizing flows
C Weilbach, B Beronov, W Harvey, F Wood
Second Symposium on Advances in Approximate Bayesian Inference, 2019
22019
Decoupling conflicts for configurable resolution in an open replication system
C Weilbach, K Kühne, A Bieniusa
arXiv preprint arXiv:1508.05545, 2015
22015
Trans-Dimensional Generative Modeling via Jump Diffusion Models
A Campbell, W Harvey, C Weilbach, V De Bortoli, T Rainforth, A Doucet
Advances in Neural Information Processing Systems 36, 2024
12024
If the Sources Could Talk: Evaluating Large Language Models for Research Assistance in History
GG Garcia, C Weilbach
arXiv preprint arXiv:2310.10808, 2023
12023
Decoupling conflict resolution with CDVCS
C Weilbach, K Kühne, A Bieniusa
Proceedings of the 2nd Workshop on the Principles and Practice of …, 2016
12016
replikativ. io: Composable consistency primitives for a scalable and robust global replication system.
C Weilbach, K Kühne, A Bieniusa
CoRR, 2015
12015
Scaling Graphically Structured Diffusion Models
CD Weilbach, W Harvey, H Shirzad, F Wood
ICML 2023 Workshop on Structured Probabilistic Inference {\&} Generative …, 2023
2023
Sequential Core-Set Monte Carlo
B Beronov, C Weilbach, F Wood, T Campbell
Uncertainty in Artificial Intelligence, 2165-2175, 2021
2021
Useful Uncertainties in Reinforcement Learning
C Weilbach
2018
Techreport: Time-sensitive probabilistic inference for the edge
C Weilbach, A Bieniusa
arXiv preprint arXiv:1710.11057, 2017
2017
The system can't perform the operation now. Try again later.
Articles 1–15