What’s coming up at #ICML2021?

The thirty eighth International Conference on Machine Learning (ICML) is now underway and will run for the entirety of this week (18 – 24 July), in a virtual only format. There will five invited talks to enjoy, as well as workshops, tutorials, affinity events and socials. Find out more below:

Invited talks

Daphne Koller – Rethinking Drug Discovery in the Era of Digital Biology
Xiao Cunde, Qin Dahe – Cryospheric Science and Emergence of Machine Learning
Ester Duflo – Title to be confirmed
Edward Chang – Encoding and Decoding Speech From the Human Brain
Cecilia Clementi – Machine Learning for Molecular Science

Workshops

Challenges in Deploying and monitoring Machine Learning Systems
INNF+: Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models
ICML Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI
Tackling Climate Change with Machine Learning
Theory and Foundation of Continual Learning
ICML 2021 Workshop on Unsupervised Reinforcement Learning
Human-AI Collaboration in Sequential Decision-Making
ICML Workshop on Representation Learning for Finance and E-Commerce Applications
Reinforcement Learning for Real Life
Uncertainty and Robustness in Deep Learning
Interpretable Machine Learning in Healthcare
8th ICML Workshop on Automated Machine Learning (AutoML 2021)
Theory and Practice of Differential Privacy
The Neglected Assumptions In Causal Inference
Machine Learning for Data: Automated Creation, Privacy, Bias
ICML Workshop on Human in the Loop Learning (HILL)
ICML Workshop on Algorithmic Recourse
A Blessing in Disguise: The Prospects and Perils of Adversarial Machine Learning
International Workshop on Federated Learning for User Privacy and Data Confidentiality in Conjunction with ICML 2021 (FL-ICML’21)
Workshop on Socially Responsible Machine Learning
ICML 2021 Workshop on Computational Biology
Subset Selection in Machine Learning: From Theory to Applications
Workshop on Computational Approaches to Mental Health @ ICML 2021
Workshop on Distribution-Free Uncertainty Quantification
Information-Theoretic Methods for Rigorous, Responsible, and Reliable Machine Learning (ITR3)
Beyond first-order methods in machine learning systems
Self-Supervised Learning for Reasoning and Perception
Time Series Workshop
Workshop on Reinforcement Learning Theory
Over-parameterization: Pitfalls and Opportunities

Tutorials

From ML research to ML products: A path towards building models with real-world impact
Natural-XAI: Explainable AI with Natural Language Explanations
Continual Learning with Deep Architectures
Sparsity in Deep Learning: Pruning and growth for efficient inference and training
Synthetic Healthcare Data Generation and Assessment: Challenges, Methods, and Impact on Machine Learning
Responsible AI in Industry: Practical Challenges and Lessons Learned
Online and non-stochastic control
Unsupervised Learning for Reinforcement Learning
Random Matrix Theory and ML (RMT+ML)
Social Implications of Large Language Models
Privacy in learning: Basics and the interplay
Self-Attention for Computer Vision

Affinity events

Women in Machine Learning (WiML) Un-Workshop
LatinX in AI (LXAI) Research at ICML 2021
Black in AI Social
LatinX in AI Social
Queer in AI Social: AI for Biodiversity
LatinX in AI, Queer in AI, WiML – Joint Poster Session
Indigenous in AI Social
Queer in AI Workshop
Queer in AI Social: Storytelling: Intersectional Queer Experiences Around the World

Lucy Smith , Managing Editor for AIhub.

Lucy Smith , Managing Editor for AIhub.