43 citations · 49 across the 9 of their papers we have counts for
4 papers · 1 filter
KITE: A Knowledge-Injected Temporal Encoder for Time-Series Event Forecasting
Jonas Petersen, Pratik Jawahar, Riccardo Maggioni +6
Forecasting rare, high-cost events in multivariate time-series systems is hard because their precursors are seldom observed, so a purely data-driven model has little to learn from.…
CHLU: The Causal Hamiltonian Learning Unit as a Symplectic Primitive for Deep Learning
Pratik Jawahar, Maurizio Pierini
Current deep learning primitives dealing with temporal dynamics suffer from a fundamental dichotomy: they are either discrete and unstable (LSTMs) \citep{pascanu_difficulty_2013},…
Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision
Thea Klaeboe Aarrestad, Alaa Abdelhamid, Haider Abidi +457
Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape co…
SMARTHEP: training PhD students in real-time analysis at the LHC and in industry
Johannes Albrecht, Laura Boggia, Leon Bozianu +18
In this invited Editorial for Software and Computing for Big Science, we describe the SMARTHEP Innovative Training Network funded via the Marie Skłodowska-Curie Actions between 202…