We at LLNL are excited to be part of the dynamic data science community, and we look forward to meeting new colleagues and learning from each other at these events.
Upcoming Events
Conference on Neural Information Processing Systems (NeurIPS)
December 9–15, 2024
Vancouver, BC, Canada
Workshop: ML and the Physical Sciences
Papers: GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations; On the Use of Anchoring for Training Vision Models; Transformers Can Do Arithmetic with the Right Embeddings; Scalable Physics-Guided Data-Driven Component Model Reduction for Steady Navier-Stokes Flow
3rd World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2025)
June 15–19, 2025
Anaheim, CA
Committee: Youngsoo Choi
Past Events
DOE Data Days (D3)
October 22–24, 2024
Livermore, CA
European Conference on Computer Vision (ECCV)
September 29–October 4, 2024
Milan, Italy
Paper: Leveraging Hierarchical Feature Sharing for Efficient Dataset Condensation
Monterey Data Conference
August 19–22, 2024
Monterey, CA
SPIE Optics + Photonics, Applications of Machine Learning Conference
August 18–22, 2024
San Diego, CA
Planning committee: Mike Zelinski, Cindy Gonzales
International Joint Conference on Artificial Intelligence (IJCAI)
August 3–5, 2024
Jeju Island, South Korea
AI for Critical Infrastructure Workshop: Felipe Leno da Silva, Ruben Glatt
International Conference on Machine Learning (ICML)
July 21–27, 2024
Vienna, Austria
Papers: Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies; Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression; TrustLLM: Trustworthiness in Large Language Models; PAGER: Accurate Failure Characterization in Deep Regression Models
Conference on Machine Learning and Systems (MLSys)
May 13–16, 2024
Santa Clara, CA
Paper: Q-Hitter: a better token oracle for efficient LLM inference via sparse-quantized KV cache
International Conference on Learning Representations (ICRL)
May 7–11, 2024
Vienna, Austria
Papers: DeepZero: scaling up zeroth-order optimization for deep model training; NEFTune: noisy embeddings improve instruction finetuning; Scaling compute is not all you need for adversarial robustness; Accurate and scalable estimation of epistemic uncertainty for graph neural networks
Women in Data Science (WiDS) Datathon & Livermore Conference
February 28 & March 13, 2024
Livermore, CA
Host: LLNL
SIAM Conference on Uncertainty Quantification (UQ24)
February 27 – March 1, 2024
Trieste, Italy
Sessions: Uncertainty Quantification, Robustness, and Trustworthiness in Foundation Models for Scientific Research and Beyond, Parts I and II; Why One Single Surrogate Model Cannot Be Used for All Applications
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
January 4–8, 2024
Waikoloa, HI
Poster: On the Fly Neural Style Smoothing for Risk-Averse Domain Generalization