Adrià Garriga-Alonso

According to our database, Adrià Garriga-Alonso authored at least 11 papers between 2019 and 2023.

Collaborative distances:

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

2023

Towards Automated Circuit Discovery for Mechanistic Interpretability.

Arthur Conmy, Augustine N. Mavor-Parker, Aengus Lynch, Stefan Heimersheim, Adrià Garriga-Alonso

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Santilli, Andreas Stuhlmüller, Andrew M. Dai, Andrew La, Andrew K. Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakas, et al.

CoRR, 2022

Data augmentation in Bayesian neural networks and the cold posterior effect.

Seth Nabarro, Stoil Ganev, Adrià Garriga-Alonso, Vincent Fortuin, Mark van der Wilk, Laurence Aitchison

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Bayesian Neural Network Priors Revisited.

Vincent Fortuin, Adrià Garriga-Alonso, Sebastian W. Ober, Florian Wenzel, Gunnar Rätsch, Richard E. Turner, Mark van der Wilk, Laurence Aitchison

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

<i>BNNpriors</i>: A library for Bayesian neural network inference with different prior distributions.

Vincent Fortuin, Adrià Garriga-Alonso, Mark van der Wilk, Laurence Aitchison

Softw. Impacts, 2021

BNNpriors: A library for Bayesian neural network inference with different prior distributions.

Vincent Fortuin, Adrià Garriga-Alonso, Mark van der Wilk, Laurence Aitchison

CoRR, 2021

Bayesian Neural Network Priors Revisited.

Vincent Fortuin, Adrià Garriga-Alonso, Florian Wenzel, Gunnar Rätsch, Richard E. Turner, Mark van der Wilk, Laurence Aitchison

CoRR, 2021

Exact Langevin Dynamics with Stochastic Gradients.

Adrià Garriga-Alonso, Vincent Fortuin

CoRR, 2021

Correlated weights in infinite limits of deep convolutional neural networks.

Adrià Garriga-Alonso, Mark van der Wilk

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Understanding Variational Inference in Function-Space.

David R. Burt, Sebastian W. Ober, Adrià Garriga-Alonso, Mark van der Wilk

CoRR, 2020

2019

Deep Convolutional Networks as shallow Gaussian Processes.

Adrià Garriga-Alonso, Carl Edward Rasmussen, Laurence Aitchison

Proceedings of the 7th International Conference on Learning Representations, 2019