Top Tweets for #l4dc
π Congratulations to LIDS graduate students Andrea Goertzen and Sunbochen Tang, and @NavidAzizan on receiving the 2026 #L4DC Best Paper Award for "ECO: Energy-Constrained Operator Learning for Chaotic Dynamics with Boundedness Guarantees."
Learn more: https://t.co/90oHSKZPZ7
π $L4DC
π° $17.6K β $132K MC β ~7.5Γ profit on my call! ππ₯
Early entry, clean send, Alpha TG eating as usual.
CA: Fc1LDPwwcGg2nrKzzfJ8p7iprdSFvDU5WpHkgLNUpump
π₯ Join and DM for the next play.
#solana #L4DC #AlphaCalls #Winning
$L4DC
$17.6K
Fc1LDPwwcGg2nrKzzfJ8p7iprdSFvDU5WpHkgLNUpump
#solana
Looking forward to present MS-HGNN at #L4DC next week in Ann Arbor. Come to say hi if you are around π€π
It's Friday afternoon, and weβre packing for L4DC 2025 @l4dc_conf next week π
Excited to share MS-HGNN β our take on bringing morphological symmetry into GNNs for legged robot dynamics.
𧡠(1/4) We bake both kinematics and morphological symmetry into the model β
- Generalizable
- Sample-efficient
- Compact
π Project: https://t.co/1qIqrl0ziX
π arXiv: https://t.co/PEgBaIQKj1
π» Code: https://t.co/Ykb7yXQK1H
Team: @xie_fengze32905, @SizheWei, Yue Song, @yisongyue, @ganlumomo
See you next week in Ann Arbor! #Robotics #L4DC2025 #GeorgiaTech
Update: The PC for #L4DC 2025 has decided to extend the submission deadline to December 1st (AoE)! Looking forward to seeing your submissions and please encourage your colleagues, students and friends to join us too!
Reminder: 4 more weeks to the submission deadline (Nov 22) for #L4DC 2025 in Ann Arbor, MI!
Please help to spread the word and encourage your colleagues, students, and friends to submit their best work!
More info at https://t.co/pMIGidOCZn or contact us at [email protected]
8 more weeks to the submission deadline for #L4DC 2025 in Ann Arbor, MI!
Please help to widely circulate this CFP and encourage your colleagues, students, and friends to submit their best work!
Further information at https://t.co/pMIGidOCZn or contact us at [email protected]
#L4DC Keynote: βInductive Biases for Robot Reinforcement Learningβ by
Jan Peters (@TUDarmstadt) at @l4dc_conf
#L4DC Keynote: βThe state of optimal and learning control in the 2020sβ by
Jonas Buchli (@GoogleDeepMind) at @l4dc_conf
Yesterday's L4DC schedule was very exciting - with plenary talks by Shankar Sastry (UC Berkeley), Na Li (Harvard) and Mary Dunlop (Boston University). An equally exciting day ahead! #l4dc
Excited to present our work at #L4DC: "Dynamics Harmonic Analysis of Robotic Systems: Application in Data-Driven Koopman Modelling".
Join us at our poster session on Wed at 16:15!
π Website and code: https://t.co/1IF8ZIYhXvπ· Paper: https://t.co/AzQa39anT9
In our #L4DC paper, we propose a method for teaching agents with varying characteristics, such as different kinematics and dynamics, through learning from demonstration. We propose that the teacher agent should consider the "surprise" PERCEIVED by the student agent.
I'll be presenting our recent paper "Adaptive teaching in heterogeneous agents: Balancing surprise in sparse reward scenarios" at L4DC Poster Session 1 this Tuesday.
paper: https://t.co/vwxPTWVZhW
This work was a collaboration with Emma Clark and Prof.@negar_mehr.
Flying to Oxford tomorrow for #L4DC to present the "sister paper" of CLOSURE, where we use SOS relaxations to find outer approximations of uncertainty sets!
Two more tutorial sessions on "Learning under Requirements: Supervised and Reinforcement Learning with Constraints" and "Safety Filters for Control: Concepts, Theory and Practice" this afternoon. https://t.co/o7EfxPloU7 #l4dc
Congrats to Fernando, Haruki, and the team on the best paper award π₯ at #L4DC for iDBF: https://t.co/v4TwD2AJLx, bringing control barrier functions to learned high-dimensional latent spaces, enabling visuomotor policies to avoid drifting out of distribution π₯³ @ToyotaResearch
Super excited that our latest work received the Best Paper Award at #L4DC! Listen to Fernando's oral presentation tomorrow afternoon if you're attending, who delivered the awesome work during his internship last year at TRI. As his mentor, it's such a great honor for me too!
Super excited that our latest work received the Best Paper Award at #L4DC! Listen to Fernando's oral presentation tomorrow afternoon if you're attending, who delivered the awesome work during his internship last year at TRI. As his mentor, it's such a great honor for me too!
Check out our #L4DC paper on learning policy-aware dynamics model for reinforcement learning!
The idea is very simple: focus model learning on the current policyβs visitation distribution. We theoretically show why this is desirable and extend the dual RL paradigm to MBRL, resulting in a simple, practical algorithm, TOM!
Excited to share our our #L4DC2023 paper that introduces "Transition Occupancy Matching"(TOM)
TOM learns a dynamics model that keeps up with the improving policy, facilitating continued progress
Paper π°: https://t.co/JQhFPro8Zi
Code π»: https://t.co/ZI6MVUZdU5
π§΅
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