What’s coming up at #NeurIPS2023?

The thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023) is due to kick-off on Sunday 10 December and run until Saturday 16 December. There is a bumper programme of events, including invited talks, orals, posters, tutorials, workshops, and socials, not to mention AIhub’s session on science communication.

Invited talks

There are seven invited talks this year.

Björn Ommer – NextGenAI: The Delusion of Scaling and the Future of Generative AI
Lora Aroyo – The Many Faces of Responsible AI
Linda Smith – Coherence statistics, self-generated experience and why young humans are much smarter than current AI
Jelani Nelson – Sketching: core tools, learning-augmentation, and adaptive robustness
Alexander Rush, Aakanksha Chowdhery, Angela Fan, Percy Liang, Jie Tang – Beyond Scaling (panel discussion)
Christopher Ré – Systems for Foundation Models, and Foundation Models for Systems
Susan Murphy – Online Reinforcement Learning in Digital Health Interventions

Affinity group workshops

The following affinity group workshops will take place on Monday 11 December:

• Black in AI
• Global South in AI
• Queer in AI
• LatinX in AI
• Women in Machine Learning
• North Africans in AI
• Muslims in ML
• New in ML
• Indigenous in AI/ML

Tutorials

For this year’s conference, there will be a total of 14 tutorials. These will be held on Monday 11 December, in person only.

• How to Work With Real Humans in Human-AI Systems, Elizabeth Bondi-Kelly, Krishnamurthy Dvijotham, Matthew Taylor
• Governance & Accountability for ML: Existing Tools, Ongoing Efforts, & Future Directions, Emily Black, Hoda Heidari, Dan Ho
• Latent Diffusion Models: Is the Generative AI Revolution Happening in Latent Space?, Karsten Kreis, Ruiqi Gao, Arash Vahdat
• Data Contribution Estimation for Machine Learning, Stephanie Schoch, Ruoxi Jia, Yangfeng Ji
• Contributing to an Efficient and Democratized Large Model Era, James Demmel, Yang You
• Recent and Upcoming Developments in Randomized Numerical Linear Algebra for ML, Michał Dereziński, Michael Mahoney
• Language Models Meet World Models, Zhiting Hu, Tianmin Shu
• Do You Prefer Learning with Preferences?, Aditya Gopalan, Aadirupa Saha
• Data-Centric AI for reliable and responsible AI: from theory to practice, Mihaela van der Schaar, Isabelle Guyon, Nabeel Seedat
• What can we do about NeurIPS Reviewer #2? Challenges, Solutions, Experiments and Open Problems in Peer Review, Nihar Shah
• Reconsidering Overfitting in the Age of Overparameterized Models, Spencer Frei, Vidya Muthukumar, Fanny Yang
• Exploring and Exploiting Data Heterogeneity for Prediction and Decision-Making, Peng Cui, Hongseok Namkoong, Jiashuo Liu, Tiffany Cai
• Machine Learning for Theorem Proving, Emily First, Albert Q. Jiang, Kaiyu Yang
• Application Development using Large Language Models, Andrew Ng, Isa Fulford

Find out more about the tutorials here.

Science communication for AI researchers – a quick introduction

We will be running a short course on science communication, on Monday 11 December. Find out more here.

Workshops

There will be a total of 58 workshops. These will be held on Friday 15 and Saturday 16 December:

• Deep Generative Models for Health
• New Frontiers of AI for Drug Discovery and Development
• Generative AI for Education (GAIED): Advances, Opportunities, and Challenges
• Information-Theoretic Principles in Cognitive Systems (InfoCog)
• UniReps: Unifying Representations in Neural Models
• Touch Processing: a new Sensing Modality for AI
• AI for Accelerated Materials Design (AI4Mat-2023)
• Foundation Models for Decision Making
• Associative Memory & Hopfield Networks in 2023
• NeurIPS 2023 Workshop: Machine Learning and the Physical Sciences
• Causal Representation Learning
• Machine Learning in Structural Biology Workshop
• Table Representation Learning Workshop
• Instruction Tuning and Instruction Following
• AI meets Moral Philosophy and Moral Psychology: An Interdisciplinary Dialogue about Computational Ethics
• Computational Sustainability: Promises and Pitfalls from Theory to Deployment
• Attributing Model Behavior at Scale (ATTRIB)
• Workshop on robustness of zero/few-shot learning in foundation models (R0-FoMo)
• NeurIPS 2023 Workshop on Diffusion Models
• Backdoors in Deep Learning: The Good, the Bad, and the Ugly
• Heavy Tails in ML: Structure, Stability, Dynamics
• Agent Learning in Open-Endedness Workshop
• OPT 2023: Optimization for Machine Learning
• MATH-AI: The 3rd Workshop on Mathematical Reasoning and AI
• Goal-Conditioned Reinforcement Learning
• Algorithmic Fairness through the Lens of Time
• Workshop on Distribution Shifts: New Frontiers with Foundation Models
• New Frontiers in Graph Learning (GLFrontiers)
• 6th Workshop on Artificial Intelligence for Humanitarian Assistance and Disaster Response
• AI for Science: from Theory to Practice
• NeurIPS 2023 Workshop on Machine Learning for Creativity and Design
• Third Workshop on Efficient Natural Language and Speech Processing (ENLSP-III): Towards the Future of Large Language Models and their Emerging Descendants
• Workshop on Advancing Neural Network Training (WANT): Computational Efficiency, Scalability, and Resource Optimization
• Temporal Graph Learning Workshop @ NeurIPS 2023
• NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning: Blending New and Existing Knowledge Systems
• Adaptive Experimental Design and Active Learning in the Real World
• Generalization in Planning (GenPlan ’23)
• Generative AI and Biology (GenBio@NeurIPS2023)
• Gaze Meets ML
• 6th Robot Learning Workshop: Pretraining, Fine-Tuning, and Generalization with Large Scale Models
• Intrinsically Motivated Open-ended Learning (IMOL) Workshop
• Machine Learning for Audio
• Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS 2023 (FL@FM-NeurIPS’23)
• The Symbiosis of Deep Learning and Differential Equations — III
• Socially Responsible Language Modelling Research (SoLaR)
• Optimal Transport and Machine Learning
• I Can’t Believe It’s Not Better (ICBINB): Failure Modes in the Age of Foundation Models
• Mathematics of Modern Machine Learning (M3L)
• XAI in Action: Past, Present, and Future Applications
• Regulatable ML: Towards Bridging the Gaps between Machine Learning Research and Regulations
• Machine Learning for Systems
• Symmetry and Geometry in Neural Representations
• Synthetic Data Generation with Generative AI
• 4th Workshop on Self-Supervised Learning: Theory and Practice
• Multi-Agent Security: Security as Key to AI Safety
• Medical Imaging meets NeurIPS
• Learning-Based Solutions for Inverse Problems
• Machine Learning with New Compute Paradigms

Find out more about the workshops here.

Accepted papers and other events

• Accepted paper list
• Datasets and benchmarks track
• Competition track
• Socials

Lucy Smith , Managing Editor for AIhub.

Lucy Smith , Managing Editor for AIhub.