NVIDIA at NeurIPS

NVIDIA at NeurIPS 2026:

AI Research, Papers & Open-Source Demos

December 6–12 | Sydney, Australia
December 9–13 | Atlanta, Georgia
December 9–13 | Paris, France

NVIDIA returns to NeurIPS 2026 with accepted papers, workshops, and open-source releases spanning physical AI, robotics, generative models, healthcare, and financial services. Join us December 6–12 in Sydney, December 9–13 in Atlanta, or December 9–13 in Paris. Register now and explore NVIDIA's latest AI research.

Stay tuned for updates on accepted papers, workshops, open-code releases, and on-site events.

Which NVIDIA Research Papers and Workshops Will Be Presented at NeurIPS 2026?

Check back in October for updates, and browse last year’s NVIDIA research across AI focus areas.

How is NVIDIA Advancing AI Research Across Key Frontiers?

NVIDIA Nemotron

Learn how open source AI technology like NVIDIA Nemotron™ provides the transparency and trust businesses need to successfully adopt AI.

Reinforcement Learning Pretraining (RLP)

Bring reinforcement learning directly into the pretraining stage, rewarding models for generating useful chains-of-thought (CoT) that actually help predict future tokens.

How Open Source Makes AI Better

Hear from NVIDIA leaders Bryan Catanzaro and Jonathan Cohen about why open source isn’t just an option, but the essential engine for solving your toughest enterprise problems.

World Models

NVIDIA Cosmos™ is a platform purpose-built for physical AI, featuring state-of-the-art generative world foundation models, guardrails, and an accelerated data processing and curation pipeline.

Robotics Research and Development Digest (R²D²)

Discover the R²D² blog for insights into robotics AI breakthroughs and advanced workflows, and leverage the NVIDIA Isaac™ platform for simulation tools to speed up your robotics research and take on real-world challenges.

NVIDIA Omniverse

Accelerate Autonomous Vehicle (AV) Simulation With Neural Reconstruction and World Foundation Models

NVIDIA’s Omniverse™ and Cosmos platforms leverage neural reconstruction, foundation models, and advanced data workflows to drive AV simulation and validation, enabling scalable generation, curation, and diversification of synthetic sensor datasets for AI research and deployment.

La-Proteina

La-Proteina is the first generative model that demonstrates accurate codesign of fully atomistic protein structures at scale, up to 800 residues, with state-of-the-art atomistic motif scaffolding performance.

Kinetic GROVER Multi-Task (KERMT)

KERMT is an enhanced reimplementation of the GROVER model, uses PyTorch Distributed Data Parallel for distributed pretraining, automates hyperparameter tuning, and accelerates fine-tuning and prediction using cuik-molmaker.

nvMolKit

nvMolKit is a GPU-accelerated cheminformatics library designed to significantly speed up molecular computation tasks common in computational chemistry and drug discovery.

Protein Structure Prediction

When combined with MMseqs2-GPU on an x86 system with one NVIDIA RTX PRO™ 6000 Blackwell Server Edition GPU, deep learning inference with OpenFold and TensorRT™ is up to 131x faster.

Build Your Own Transaction Foundation Model for Financial Intelligence

Learn how the Build Your Own Transaction Foundation Model developer example helps financial institutions build embeddings using transformer architecture on tabular data.

Automating and Optimizing Financial Signal Discovery With Multi-Agent Systems

Learn how the Quantitative Signal Discovery Agent developer example allows firms to automate signal discovery—a core workflow in quantitative trading—using agentic AI.

Accelerating Real-Time Financial Decisions With Quantitative Portfolio Optimization

Learn how the Quantitative Portfolio Optimization developer example accelerates strategy testing and time to decision in financial services.

Build Efficient Financial Data Workflows With AI Model Distillation

Learn how the AI Model Distillation for Financial Data developer example enables feature engineering and faster backtesting for research in capital markets.

NVIDIA Careers

Join the NVIDIA Team Behind NeurIPS Research

Join the team behind the work at NeurIPS. We’re hiring researchers and engineers across AI, robotics, graphics, and more.

Frequently Asked Questions About NeurIPs

The Conference on Neural Information Processing Systems (NeurIPS) is one of the premier global forums for researchers and practitioners to share advancements in machine learning, neuroscience, and AI. It serves as a central venue for presenting groundbreaking research that drives the future of AI.

Explore the current conference details and research topics on the official NeurIPS website

NVIDIA focuses on showcasing research across several key AI frontiers, including accelerated computing, physical AI, robotics, generative world models, and advanced simulations for healthcare and financial services.

Browse the latest research papers and focus areas on the NVIDIA Research landing page.

NeurIPS 2026 is hosted in three global locations: Sydney, Australia, at the International Convention Centre Sydney (ICC Sydney); Atlanta, Georgia, at the Georgia World Congress Center; and Paris, France, at the Paris Convention Centre. You can find specific logistical details and site-specific schedules on the official conference portal.

View the conference schedule and venue details on the official NeurIPS registration portal.

Registration for the NeurIPS conference can be completed through the official conference portal, which provides access to workshops, tutorials, and paper presentations.

Register for the event and view the schedule at the NeurIPS registration site.

Yes, NVIDIA actively recruits researchers and engineers at NeurIPS who specialize in areas like robotics, AI, graphics, and accelerated computing to join their innovative teams.

View current open positions and build your career at NVIDIA Careers.

NVIDIA’s research labs offer resources including publications, source code, and interactive demonstrations, providing a deep dive into their advancements in AI, robotics, and graphics.

Visit the various NVIDIA Research Labs to see ongoing projects.

Explore NVIDIA Research

Explore NVIDIA labs, publications, and demos to see more of the research behind our work at NeurIPS.

Research Labs

Explore cutting-edge work from NVIDIA’s research labs, spanning AI, graphics, robotics, and autonomous systems. Access code, publications, and interactive demos.

Publications

Browse the full catalog of peer-reviewed NVIDIA papers across all conferences, journals, and preprints—searchable by topic, year, and research area.

AI Playground

Try interactive demos of our latest research in generative AI, vision, speech, and more—no setup required. See the science in action before diving into the code.

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