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Publication search results
found 65 matches
- 2024
- Wenlin Chen, Mingtian Zhang, Brooks Paige, José Miguel Hernández-Lobato, David Barber:
Diffusive Gibbs Sampling. CoRR abs/2402.03008 (2024) - Martin Marek, Brooks Paige, Pavel Izmailov:
Can a Confident Prior Replace a Cold Posterior? CoRR abs/2403.01272 (2024) - Maksym Korablyov, Cheng-Hao Liu, Moksh Jain, Almer M. van der Sloot, Eric Jolicoeur, Edward Ruediger, Andrei Cristian Nica, Emmanuel Bengio, Kostiantyn Lapchevskyi, Daniel St-Cyr, Doris Alexandra Schuetz, Victor Ion Butoi, Jarrid Rector-Brooks, Simon Blackburn, Leo Feng, Hadi Nekoei, Sai Krishna Gottipati, Priyesh Vijayan, Prateek Gupta, Ladislav Rampásek, Sasikanth Avancha, Pierre-Luc Bacon, William L. Hamilton, Brooks Paige, Sanchit Misra, Stanislaw Kamil Jastrzebski, Bharat Kaul, Doina Precup, José Miguel Hernández-Lobato, Marwin H. S. Segler, Michael M. Bronstein, Anne Marinier, Mike Tyers, Yoshua Bengio:
Generative Active Learning for the Search of Small-molecule Protein Binders. CoRR abs/2405.01616 (2024) - Daniel Tan, David Chanin, Aengus Lynch, Dimitrios Kanoulas, Brooks Paige, Adrià Garriga-Alonso, Robert Kirk:
Analyzing the Generalization and Reliability of Steering Vectors. CoRR abs/2407.12404 (2024) - Chunan Liu, Lilian Denzler, Yihong Chen, Andrew Martin, Brooks Paige:
AsEP: Benchmarking Deep Learning Methods for Antibody-specific Epitope Prediction. CoRR abs/2407.18184 (2024) - Seongho Son, William Bankes, Sayak Ray Chowdhury, Brooks Paige, Ilija Bogunovic:
Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift. CoRR abs/2407.18676 (2024) - 2023
- Stephen Law
, Rikuo Hasegawa, Brooks Paige, Chris Russell
, Andrew Elliott:
Explaining holistic image regressors and classifiers in urban analytics with plausible counterfactuals. Int. J. Geogr. Inf. Sci. 37(12): 2575-2596 (2023) - Mingtian Zhang, Alex Hawkins-Hooker, Brooks Paige, David Barber:
Moment Matching Denoising Gibbs Sampling. NeurIPS 2023 - Rohan Anil, Andrew M. Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, Eric Chu, Jonathan H. Clark, Laurent El Shafey, Yanping Huang, Kathy Meier-Hellstern, Gaurav Mishra, Erica Moreira, Mark Omernick, Kevin Robinson, Sebastian Ruder, Yi Tay, Kefan Xiao, Yuanzhong Xu, Yujing Zhang, Gustavo Hernández Ábrego, Junwhan Ahn, Jacob Austin, Paul Barham, Jan A. Botha, James Bradbury, Siddhartha Brahma, Kevin Brooks, Michele Catasta, Yong Cheng, Colin Cherry, Christopher A. Choquette-Choo, Aakanksha Chowdhery, Clément Crepy, Shachi Dave, Mostafa Dehghani, Sunipa Dev, Jacob Devlin, Mark Díaz, Nan Du, Ethan Dyer, Vladimir Feinberg, Fangxiaoyu Feng, Vlad Fienber, Markus Freitag, Xavier Garcia, Sebastian Gehrmann, Lucas Gonzalez, et al.:
PaLM 2 Technical Report. CoRR abs/2305.10403 (2023) - Mingtian Zhang, Alex Hawkins-Hooker, Brooks Paige, David Barber:
Moment Matching Denoising Gibbs Sampling. CoRR abs/2305.11650 (2023) - Mathieu Alain, So Takao, Brooks Paige, Marc Peter Deisenroth:
Gaussian Processes on Cellular Complexes. CoRR abs/2311.01198 (2023) - 2022
- Hugh Dance, Brooks Paige:
Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian Processes. AISTATS 2022: 7976-8002 - Mingtian Zhang, Tim Z. Xiao, Brooks Paige, David Barber:
Improving VAE-based Representation Learning. CoRR abs/2205.14539 (2022) - Mingtian Zhang, Oscar Key, Peter Hayes, David Barber, Brooks Paige, François-Xavier Briol:
Towards Healing the Blindness of Score Matching. CoRR abs/2209.07396 (2022) - 2021
- Brooks Paige, James Bell, Aurélien Bellet, Adrià Gascón, Daphne Ezer:
Reconstructing Genotypes in Private Genomic Databases from Genetic Risk Scores. J. Comput. Biol. 28(5): 435-451 (2021) - Alexander Camuto, Matthew Willetts, Chris C. Holmes, Brooks Paige, Stephen J. Roberts:
Learning Bijective Feature Maps for Linear ICA. AISTATS 2021: 3655-3663 - Yuge Shi, Brooks Paige, Philip H. S. Torr, N. Siddharth:
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models. ICLR 2021 - Matthew Willetts, Brooks Paige:
I Don't Need u: Identifiable Non-Linear ICA Without Side Information. CoRR abs/2106.05238 (2021) - Hugh Dance, Brooks Paige:
Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian Processes. CoRR abs/2111.04558 (2021) - Alexander Lavin, Hector Zenil, Brooks Paige, David Krakauer, Justin Gottschlich, Tim Mattson, Anima Anandkumar, Sanjay Choudry, Kamil Rocki, Atilim Günes Baydin, Carina Prunkl, Olexandr Isayev, Erik Peterson, Peter L. McMahon, Jakob H. Macke, Kyle Cranmer, Jiaxin Zhang, Haruko M. Wainwright, Adi Hanuka, Manuela Veloso, Samuel Assefa, Stephan Zheng, Avi Pfeffer:
Simulation Intelligence: Towards a New Generation of Scientific Methods. CoRR abs/2112.03235 (2021) - 2020
- Judith Clymo, Adrià Gascón, Brooks Paige, Nathanaël Fijalkow
, Haik Manukian:
Data Generation for Neural Programming by Example. AISTATS 2020: 3450-3459 - John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato:
Barking up the right tree: an approach to search over molecule synthesis DAGs. NeurIPS 2020 - Amina Mollaysa, Brooks Paige, Alexandros Kalousis
:
Goal-directed Generation of Discrete Structures with Conditional Generative Models. NeurIPS 2020 - Brooks Paige
, James Bell
, Aurélien Bellet
, Adrià Gascón, Daphne Ezer
:
Reconstructing Genotypes in Private Genomic Databases from Genetic Risk Scores. RECOMB 2020: 266-268 - Alexander Camuto, Matthew Willetts, Brooks Paige, Chris C. Holmes, Stephen J. Roberts:
Learning Bijective Feature Maps for Linear ICA. CoRR abs/2002.07766 (2020) - Yuge Shi, Brooks Paige, Philip H. S. Torr, N. Siddharth:
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models. CoRR abs/2007.01179 (2020) - Amina Mollaysa, Brooks Paige, Alexandros Kalousis:
Goal-directed Generation of Discrete Structures with Conditional Generative Models. CoRR abs/2010.02311 (2020) - Aneesh Pappu, Brooks Paige:
Making Graph Neural Networks Worth It for Low-Data Molecular Machine Learning. CoRR abs/2011.12203 (2020) - George Lamb, Brooks Paige:
Bayesian Graph Neural Networks for Molecular Property Prediction. CoRR abs/2012.02089 (2020) - John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato:
Barking up the right tree: an approach to search over molecule synthesis DAGs. CoRR abs/2012.11522 (2020)
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