papers

Publications (24)

hep-th2014

Topological Model for Domain Walls in (Super-)Yang-Mills Theories

Markus Dierigl, Alexander Pritzel

We derive a topological action that describes the confining phase of (Super-)Yang-Mills theories with gauge group , similar to the work recently carried out by Seiberg and c…

cs.LG2023

GraphCast: Learning skillful medium-range global weather forecasting

Remi Lam, Alvaro Sanchez-Gonzalez, Matthew Willson +15

Global medium-range weather forecasting is critical to decision-making across many social and economic domains. Traditional numerical weather prediction uses increased compute reso…

cs.LG2018

Fast deep reinforcement learning using online adjustments from the past

Steven Hansen, Pablo Sprechmann, Alexander Pritzel +2

We propose Ephemeral Value Adjusments (EVA): a means of allowing deep reinforcement learning agents to rapidly adapt to experience in their replay buffer. EVA shifts the value pred…

cs.CL2025

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431

In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our…

cs.CL2025

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Rohan Anil, Sebastian Borgeaud +1340

This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consist…

stat.ML2018

Memory-based Parameter Adaptation

Pablo Sprechmann, Siddhant M. Jayakumar, Jack W. Rae +7

Deep neural networks have excelled on a wide range of problems, from vision to language and game playing. Neural networks very gradually incorporate information into weights as the…