What’s happening at #NeurIPS this week?

The conference on Neural Information Processing Systems (NeurIPS) 2020 kicked off on Sunday 6th December and will run until Saturday 12th December. Here, we give a brief summary of many of the planned sessions and events for the week ahead.

The public version of the schedule can be found here. You will need to be registered to access all of the content. Note that we have included links to the public versions in this article.

Invited talks

The conference will feature seven invited talks covering a range of interesting topics.

Charles Isbell – You can’t escape hyperparameters and latent variables: machine learning as a software engineering enterprise
Jeff Shamma – Feedback control perspectives on learning
Shafi Goldwasser – Robustness, verification, privacy: addressing machine learning adversaries
Chris Bishop – The real AI revolution
Saiph Savage – A future of work for the invisible workers in AI
Marloes Maathuis – Causal learning
Anthony M Zador – The genomic bottleneck: a lesson from biology

Tutorials

A total of 16 tutorials are taking place.

Deeper Conversational AI
Sketching and streaming algorithms
Equivariant networks
There and back again: a tale of slopes and expectations
Designing learning dynamics
Beyond accuracy: grounding evaluation metrics for human-machine learning systems
Where neuroscience meets AI (and what’s in store for the future)
Practical uncertainty estimation and out-of-distribution robustness in deep learning
Offline reinforcement learning: from algorithm design to practical applications
Advances in approximate inference
Abstraction & reasoning in AI systems: modern perspectives
Policy optimization in reinforcement learning
Machine learning for astrophysics and astrophysics problems for machine learning
Federated learning and analytics: industry meets academia
Deep implicit layers: neural ODEs, equilibrium models, and differentiable optimization
Explaining machine learning predictions: state-of-the-art, challenges, and opportunities

Affinity groups workshops

There is the chance to attend workshops from these affinity groups:

New in ML
You can access the workshop webpage here.

Black in AI
You can access the workshop webpage here.

LXAI research @ NeurIPS 2020
Visit the LXAI webpage.

Queer in AI workshop @ NeurIPS 2020
Visit the Queer in AI webpage.

Muslims in ML
You can access the workshop webpage here.

Women in machine learning
You can access the workshop webpage here.

Indigenous in AI
You can access the workshop webpage here.

Workshops

Other workshops in the programme are as follows. These will take place on Friday 11th and Saturday 12th December.

Topological data analysis and beyond
You can access the workshop webpage here.

Privacy preserving machine learning – PriML and PPML joint edition
You can access the workshop webpage here.

Meta-learning
You can access the workshop webpage here.

Learning meets combinatorial algorithms
You can access the workshop webpage here.

Tackling climate change with ML
You can access the workshop webpage here.

OPT2020: Optimization for machine learning
You can access the workshop webpage here.

Advances and opportunities: machine learning for education
You can access the workshop webpage here.

Differential geometry meets deep learning (DiffGeo4DL)
You can access the workshop webpage here.

Learning meaningful representations of life (LMRL.org)
You can access the workshop webpage here.

Workshop on dataset curation and security
You can access the workshop webpage here.

Machine learning for health (ML4H): advancing healthcare for all
You can access the workshop webpage here.

Human in the loop dialogue systems
You can access the workshop webpage here.

The pre-registration experiment: an alternative publication model for machine learning research
You can access the workshop webpage here.

Differentiable computer vision, graphics, and physics in machine learning
You can access the workshop webpage here.

Causal discovery and causality-inspired machine learning
You can access the workshop webpage here.

Self-supervised learning for speech and audio processing
You can access the workshop webpage here.

Machine learning and the physical sciences
You can access the workshop webpage here.

Resistance AI workshop
You can access the workshop webpage here.

ML competitions at the grassroots (CiML 2020)
You can access the workshop webpage here.

3rd Robot learning workshop
You can access the workshop webpage here.

Workshop on deep learning and inverse problems
You can access the workshop webpage here.

Machine learning for autonomous driving
You can access the workshop webpage here.

First workshop on quantum tensor networks in machine learning
You can access the workshop webpage here.

Crowd science workshop: remoteness, fairness, and mechanisms as challenges of data supply by humans for automation
You can access the workshop webpage here.

Competition track Friday
You can access the workshop webpage here.

Object representations for learning and reasoning
You can access the workshop webpage here.

Fair AI in finance
You can access the workshop webpage here.

Deep reinforcement learning
You can access the workshop webpage here.

ML retrospectives, surveys & meta-analyses (ML-RSA)
You can access the workshop webpage here.

BabyMind: how babies learn and how machines can imitate
You can access the workshop webpage here.

KR2ML – knowledge representation and reasoning meets machine learning
You can access the workshop webpage here.

Machine learning for economic policy
You can access the workshop webpage here.

Algorithmic fairness through the lens of causality and interpretability
You can access the workshop webpage here.

Medical imaging meets NeurIPS
You can access the workshop webpage here.

Machine learning for the developing world (ML4D): improving resilience
You can access the workshop webpage here.

Biological and artificial reinforcement learning
You can access the workshop webpage here.

I can’t believe it’s not better! Bridging the gap between theory and empiricism in probabilistic machine learning
You can access the workshop webpage here.

Machine learning for engineering modeling, simulation and design
You can access the workshop webpage here.

Machine learning for creativity and design 4.0
You can access the workshop webpage here.

Cooperative AI
You can access the workshop webpage here.

International workshop on scalability, privacy, and security in federated learning (SpicyFL 2020)
You can access the workshop webpage here.

Machine learning for molecules
You can access the workshop webpage here.

Navigating the broader impacts of AI research
You can access the workshop webpage here.

Wordplay: when language meets games
You can access the workshop webpage here.

MLPH: machine learning in public health
You can access the workshop webpage here.

Beyond BackPropagation: novel ideas for training neural architectures
You can access the workshop webpage here.

Interpretable inductive biases and physically structured learning
You can access the workshop webpage here.

AI for Earth sciences
You can access the workshop webpage here.

Talking to strangers: zero-shot emergent communication
You can access the workshop webpage here.

Machine learning for mobile health
You can access the workshop webpage here.

Shared visual representations in human and machine intelligence (SVRHM)
You can access the workshop webpage here.

Second workshop on AI for humanitarian assistance and disaster response
You can access the workshop webpage here.

Machine learning for structural biology
You can access the workshop webpage here.

Consequential decisions in dynamic environments
You can access the workshop webpage here.

Competition track Saturday
You can access the workshop webpage here.

HAMLETS: human and model in the loop evaluation and training strategies
You can access the workshop webpage here.

The challenges of real world reinforcement learning
You can access the workshop webpage here.

Workshop on computer assisted programming (CAP)
You can access the workshop webpage here.

Self-supervised learning – theory and practice
You can access the workshop webpage here.

Offline Reinforcement learning
You can access the workshop webpage here.

Machine learning for systems
You can access the workshop webpage here.

Deep learning through information geometry
You can access the workshop webpage here.

COVID-19 Symposium

This year NeurIPS will host a symposium on COVID-19 to frame challenges and opportunities for the machine learning community and to foster a frank discussion on the role of machine learning. Find out more here.

Contributed papers and more

As well as all of this, there are also 1918 contributed papers that attendees can browse. There are also a selection of demonstrations, competitions and socials. You can also take part in virtual meetups, organised by local leaders from the community.

You can read in more detail about various aspects of the conference programme and organisation on the NeurIPS Medium pages.

Lucy Smith is Senior Managing Editor for AIhub.

Lucy Smith is Senior Managing Editor for AIhub.