Machine Learning for Autonomous Driving

14th December 2023, Hilton Garden Inn New Orleans Convention Center, collocated with NeurIPS


Welcome to the 2023 Symposium on Machine Learning for Autonomous Driving collocated with NeurIPS!

Autonomous vehicles (AVs) offer a rich source of high-impact research problems for the machine learning (ML) community; including perception, state estimation, probabilistic modeling, time series forecasting, gesture recognition, robustness guarantees, real-time constraints, user-machine communication, multi-agent planning, and intelligent infrastructure. Further, the interaction between ML subfields towards a common goal of autonomous driving can catalyze interesting inter-field discussions that spark new avenues of research, which this symposium aims to promote. As an application of ML, autonomous driving has the potential to greatly improve society by reducing road accidents, giving independence to those unable to drive, and even inspiring younger generations with tangible examples of ML-based technology clearly visible on local streets. All are welcome to attend! This will be the 8th event in this series. Previous workshops in 2016, 2017, 2018, 2019, 2020, 2021, 2022 enjoyed wide participation from both academia and industry.



Submission (1st round): 19th October 2023, 23:59 Anywhere on Earth:
Notification (1st round): 27th October 2023
Submission (2nd round): 16th November 2023, 23:59 Anywhere on Earth:
Notification (2nd round): 24th November 2023
Camera ready: TBD 2023


Open: 1st July 2023
Close: 1st November 2023
Notification: 10th November 2023
Video submission: 24th November 2023


Symposium event: 14th December 2023


Morning speakers

Afternoon speakers


Submission deadlines: 19th October 2023 and 16th November 2023, at 23:59 Anywhere on Earth
Submission website:
Submission format: either extended abstracts (4 pages) or full papers (up to 9 pages) anonymously using:
 •  neurips_2023_ml4ad.tex -- LaTeX template
 •  neurips_2023_ml4ad.sty -- style file for LaTeX 2e
 •  neurips_2023_ml4ad.pdf -- example PDF output
Authors may submit to either submission round and reviewers will treat both rounds equally. Some authors may prefer the earlier notification date of the first round (27 Oct) while other authors might prefer a later submission deadline (16 Nov). References and appendix should be appended into the same (single) PDF document, and do not count towards the page count.

We invite submissions on machine learning applied to autonomous driving, including (but not limited to):
 •  Foundational Driving Models
 •  Prediction and Planning for AV with LLMs
 •  Mapless Autonomous Driving
 •  Scaling Laws for Autonomous Driving
 •  Diffusion modeling for prediction, planning
 •  Closed loop training and evaluation
 •  Causal/counterfactual analysis of interactive multi-agent scenarios
 •  Human driver in the loop for interaction modeling
 •  Coordination with vehicles (V2V) or infrastructure (V2I)
 •  Uncertainty propagation through AV software pipelines
 •  Imitation learning, Reinforcement learning for AV
 •  Transfer learning (Sim2Real) and domain adaptation for autonomous driving
 •  Off-road autonomous driving
 •  Real-time inference and prediction
 •  Adaptive driving styles based on user preferences
 •  Metrics/benchmarks for autonomous driving


Q: Are dual submissions OK?
A: Yes.

Q: Will there be archival proceedings?
A: No. Submissions will be indexed nor have archival proceedings.

Q: Should submitted papers be anonymized?
A: Yes. If accepted, we will ask for a de-anonymized version to link on the website.

Q: My papers contains ABC, but not XYZ, is this good enough for a submission?
A: Submissions will be evaluated based on these reviewer questions.


The CARLA Autonomous Driving Challenge 2023 winners will present their solutions as part of the symposium. Details here.


Hilton Garden Inn New Orleans Convention Center, 1001 S Peters St, New Orleans, Louisiana 70130, United States


  • Aman Sinha

    Aman Sinha

    is a research scientist at Waymo and co-founder of Trustworthy AI, which was acquired by Waymo in 2021.

  • Nigamaa Nayakanti

    Nigamaa Nayakanti

    is a research scientist at Waymo working on behaviour prediction modeling for autonomous vehicles.

  • Lars Kunze

    Lars Kunze

    is a Departmental Lecturer in Robotics in the Oxford Robotics Institute and the Department of Engineering Science at the University of Oxford.

  • Maximilian Naumann

    Maximilian Naumann

    is a research engineer at Bosch Center for Artificial Intelligence.

  • Jiachen Li

    Jiachen Li

    is a Postdoctoral Scholar at Stanford University working on scene understanding and decision making for intelligent systems.

  • Xinshuo Weng

    Xinshuo Weng

    is a research scientist at NVIDIA Autonomous Vehicle Research.

  • Rowan McAllister

    Rowan McAllister

    is a staff research scientist at Waymo working planning for autonomous vehicles.

Challenge Organizers

  • German Ros

    German Ros

    is the Director for Intel Autonomous Agents Labs.

  • Guillermo Lopez

    Guillermo Lopez   

    is a software engineer at CVC & Embodied AI Foundation

  • Joel Moriana

    Joel Moriana   

    is a software engineer at CVC & Embodied AI Foundation

  • Vladlen Koltun

    Vladlen Koltun   

    is a Distinguished Scientist at Apple.


We thank Waymo and Toyota Research Institute for generously sponsoring this event.