67 citations · 77 across the 17 of their papers we have counts for
8 papers · 1 filter
ClimateLLM: Efficient Weather Forecasting via Frequency-Aware Large Language Models
Shixuan Li, Wei Yang, Peiyu Zhang +6
Weather forecasting is crucial for public safety, disaster prevention and mitigation, agricultural production, and energy management, with global relevance. Although deep learning…
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain
Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna +70
This paper describes the 2nd edition of the ICML Topological Deep Learning Challenge that was hosted within the ICML 2024 ELLIS Workshop on Geometry-grounded Representation Learnin…
End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning
Yao Xiao, Guixiang Ma, Nesreen K. Ahmed +4
To enable heterogeneous computing systems with autonomous programming and optimization capabilities, we propose a unified, end-to-end, programmable graph representation learning (P…
Multiwavelet-based Operator Learning for Differential Equations
Gaurav Gupta, Xiongye Xiao, Paul Bogdan
The solution of a partial differential equation can be obtained by computing the inverse operator map between the input and the solution space. Towards this end, we introduce a \te…
Non-Markovian Reinforcement Learning using Fractional Dynamics
Gaurav Gupta, Chenzhong Yin, Jyotirmoy V. Deshmukh +1
Reinforcement learning (RL) is a technique to learn the control policy for an agent that interacts with a stochastic environment. In any given state, the agent takes some action, a…
Learning Hyperbolic Representations of Topological Features
Panagiotis Kyriakis, Iordanis Fostiropoulos, Paul Bogdan
Learning task-specific representations of persistence diagrams is an important problem in topological data analysis and machine learning. However, current state of the art methods…