Spencer M. Richards

[Masha Itkina @MashaItkina]

Thanks to everyone who came to my talk today and for all the questions!

If you want to hear my thoughts on whether scale is enough for robot deployment, come by the debate in room B2 at 4:15 pm CST!

[Masha Itkina @MashaItkina]

Excited to talk about robot generalization on Saturday at 08:20 - 08:45 am at the 6th Robot Learning Workshop. If you are @NeurIPSConf for the next few days, reach out and I am happy to chat/catch up!

[Spencer M. Richards @spenMrich]

I’ll be at poster 707 in a few minutes, and at Oral C2 later around 4:12pm HST!

[Spencer M. Richards @spenMrich]

Excited to present "Learning Control-Oriented Dynamical Structure from Data" next week at #ICML2023!

We enforce factorized structure in learned dynamics models to enable performant nonlinear control.

Paper: https://t.co/f79wPtohz9
Code (w/ #JAX): https://t.co/jqorikwxt5

[Massachusetts Institute of Technology (MIT) @MIT]

A new machine-learning technique can efficiently learn to control a robot, leading to better performance. Using this method, “we’re able to naturally create controllers that function much more effectively in the real world,” Navid Azizan says. https://t.co/bkSQV8ylLH

[Spencer M. Richards @spenMrich]

If you're around at #ICML2023 next week on Thursday, drop by to chat! I'll be at a poster and giving an oral presentation later!

ICML schedule: https://t.co/6C8qmAdLsi

[Spencer M. Richards @spenMrich]

Excited to present "Learning Control-Oriented Dynamical Structure from Data" next week at #ICML2023!

We enforce factorized structure in learned dynamics models to enable performant nonlinear control.

Paper: https://t.co/f79wPtohz9
Code (w/ #JAX): https://t.co/jqorikwxt5

[Spencer M. Richards @spenMrich]

A huge thanks to all co-authors!
- J.-J. Slotine and @NavidAzizan at @MIT
- @drmapavone at @StanfordEng / @StanfordASL

[Daniele Gammelli @DanieleGammelli]

Exciting first day co-teaching @drmapavone’s AA203: Optimal and Learning-Based Control, with @spenMrich at @StanfordEng!

Interested in the intersections between optimal control and RL? Look no further, all course materials will be available at: https://t.co/hMNP0sEhbz

[Rohan Sinha @RohanSinhaSU]

Out-of-distribution inputs derail predictions of ML models. How can we cope with OOD data in robotics? How do we even define what makes data OOD?

We provide a perspective paper arguing a system-level view of OOD data in robotics! 🧵 (1/5)

Now on Arxiv: https://t.co/gxJPeXLynG

[Masha Itkina @MashaItkina]

Excited to present our work with @aiprof_mykel on "Interpretable Self-Aware Neural Networks for
Robust Trajectory Prediction" @corl_conf! Come by our poster (paper #54) at Poster Session 4, 4:05-5:20 pm NZDT tomorrow!

Paper: https://t.co/9N8YPCxxiH
Code: https://t.co/wyMEofTVm9

[Masha Itkina @MashaItkina]

So excited to hold our 5th Robot Learning Workshop @NeurIPSConf this year on Trusworthy Robotics on Dec. 9th!

[James Harrison @jmes_harrison]

New on arXiv: we present a learning control approach capable of safe and efficient online adaptation. Our approach combines elements of classical adaptive control, modern robust MPC, and Bayesian meta-learning to yield guaranteed-safe online adaptation! https://t.co/rxXzHMm06H 🧵

[Masha Itkina @MashaItkina]

Thank you to everyone who attended my successful PhD defense yesterday on "Uncertainty-Aware Spatiotemporal Perception for Autonomous Vehicles"! The recording is now up on YouTube: https://t.co/1mvlItGfo3

[Spencer M. Richards @spenMrich]

Happening now!

[Spencer M. Richards @spenMrich]

Can we learn dynamics model features offline for better online adaptation?

Check out Adaptive-Control-Oriented Meta-Learning at #RSS2021 (Tues. and Thurs.)!
https://t.co/cfJ7c60rOH

w/ @NavidAzizan, J.-J. Slotine, and @MarcoPavoneSU

Code (w/ #JAX): https://t.co/UDwg7LDCMF

[Spencer M. Richards @spenMrich]

Can we learn dynamics model features offline for better online adaptation?

Check out Adaptive-Control-Oriented Meta-Learning at #RSS2021 (Tues. and Thurs.)!
https://t.co/cfJ7c60rOH

w/ @NavidAzizan, J.-J. Slotine, and @MarcoPavoneSU

Code (w/ #JAX): https://t.co/UDwg7LDCMF