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ICLR 2023

Announcing ICLR 2023 Keynote Speakers

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By ICLR 2023 Senior Program Chair Been Kim and Program Chairs Maximilian Nickel, Mengdi Wang, Nancy F Chen, Vukosi Marivate

We are thrilled to host the following keynote speakers at ICLR 2023:

  • Elaine O. Nsoesie (Boston University School of Public Health and Center for Antiracist Research)
  • Sofia Crespo
  • Masashi Sugiyama (RIKEN / The University of Tokyo) 
  • Girmaw Abebe Tadesse (IBM Research)
  • Jascha Sohl-Dickstein (Google Brain)
  • Dilek Hakkani-Tur (stealth AI startup)

The keynote talks will cover a diverse set of research topics, ranging from generative models,

ML in health care and health equity, Statistical ML/theory, to Conversational AI and AI for creativity. All invited talks will be in-person, 60 min talk including a live Q&A. We hope that the talks will provoke us into thinking deeply about both the technical foundations of deep learning and its increasing impact on society.

We solicited keynote speaker nominations from area chairs and senior area chairs of ICLR 2022 as well as the public. Among more than 70+ nominations, we prioritized candidates who not only have conducted exciting research but also have contributed to diversity in the community. We would like to thank all ACs/SACs who submitted nominations of excellent speaker candidates.

We cannot wait to see the invited talks in-person and participate in the live Q&A at Rwanda.

Announcing the Accepted Workshops at ICLR 2023

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By ICLR 2023 Workshop Chairs, Aisha Walcott-Bryant, Celia Cintas, Hang Zhao, Rose Yu

We want to thank everyone who submitted a workshop proposal to ICLR. We were very impressed by the quality of the proposals and thrilled to be able to include some of them as a part of the ICLR 2023 program. This year, we received 51 submissions and accepted 21 hybrid/in-person and 5 fully virtual workshops. 

We also want to thank our teams of reviewers, the ICLR program committee, and the ICLR 2023 Chairs for their kind support.

Selection Process

Ultimately, we could not accept every proposal, but we worked to balance a few goals. We wanted a good representation of theory, applications, and innovative multidisciplinary workshops to broaden the ICLR community. We also aimed to promote diversity, broadening geographic, gender, institutions, and seniority in the organization team and the invited speakers. Additionally, in this call for workshop proposals, we included the option for different modalities, such as hybrid, in-person, and fully virtual workshops.

This year, we will have two days for workshops on May 4th and May 5th 2023. To attract a diverse audience and encourage attendance,  we tried to avoid having workshops with very similar or narrow topics.

We look forward to all your contributions to the workshops!

Accepted In-Person/Hybrid Workshops

Tackling Climate Change with Machine Learning: Global Perspectives and Local Challenges
Neural Fields across Fields: Methods and Applications of Implicit Neural Representations
4th Workshop on African Natural Language Processing (AfricaNLP 2023)
Mathematical and Empirical Understanding of Foundation Models (ME-FoMo)
Machine Learning for Drug Discover (MLDD)
ICLR 2023 Workshop on Machine Learning for Remote Sensing
AI for Agent-Based Modelling (AI4ABM)
Accelerating Model Driven Discovery with ML
Neurosymbolic Generative Models (NeSy-GeMs)
Reincarnating Reinforcement Learning
Physics for Machine Learning
Time Series Representation Learning for Health
First workshop on “Machine Learning & Global Health”
Machine Learning for IoT: Datasets, Perception, and Understanding
Pitfalls of limited data and computation for Trustworthy ML
Trustworthy and Reliable Large-Scale Machine Learning Models
ICLR 2023 Workshop on Sparsity in Neural Networks: On practical limitations and tradeoffs between sustainability and efficiency
Scene Representations for Autonomous Driving
Multimodal Representation Learning (MRL): Perks and Pitfalls
4th Workshop on practical ML for Developing Countries: learning under limited/low resource settings
First Workshop on Social Influence in Natural Language Processing (SocInf-NLP 2023)

Accepted Virtual Workshops

Trustworthy Machine Learning in Healthcare
From Molecules to Materials: ICLR 2023 Workshop on Machine learning for materials (ML4Materials)
What do we need for successful domain generalization?
Backdoor Attacks and Defenses in Machine Learning
Deep Learning for Code (DL4C)