I'm at #NeurIPS2022 too! #causality #causal representation learning and how #causality helps for #distribution shifts 💥 Wed at 2pm: Poster on how (causal) graphs help adapt to nonstationarity: Fan Feng Biwei Huang Kun Zhang-in pursuit of Causality with ML neurips.cc/Conferences/20… Sat all day: Causal view on Dynamic Systems Workshop @NeurIPS22

Causal Representation Learning meets #Embodied-AI: excited to share 🍪BISCUIT, accepted at #uai2023 UAI 2025! BISCUIT learns #causal variables from videos using low-level actions in robotic environments. 📜: arxiv.org/abs/2306.09643 🖥️: phlippe.github.io/BISCUIT/ 🧵 1/10

🚨CFP #Causal #Representation #Learning NeurIPS Conference 2023 WS🚨 Do you have ideas on how to learn #causal representations from raw data, e.g. images, #abstract #macro variables or leverage #causality in #ML? Then submit a max 6 pg paper to our workshop crl-workshop.github.io

Stay tuned for our upcoming workshop call for papers, 'ICBINB: Failure Modes in the Age of Foundation Models' at NeurIPS 2023. Excited to foster enriching discussions and explore breakthroughs together. See you there! #NeurIPS2023 #ICBINB

One month (until Oct 2 at 23:59 AoE) to submit to our #NeurIPS2023 workshop on #causal #representation #learning, connecting the #causality and representation learning communities 🚀 Have ideas in this domain? Submit max 6 pages of unpublished research at openreview.net/group?id=NeurI…

Excited to share that our work "Learning dynamic Attribute-factored world models for efficient multi-object RL" has been accepted at NeurIPS 2023! A thread will come soon!

Excited to reunite with everyone at #NeurIPS2023 next month! Don't forget to check out our workshop I Can't Believe It's Not Better! on the failure modes of foundation models: shorturl.at/qrtJM (Looks like we added one more foundation model failure mode after last weekend!) 🤓

A massive thank you to everyone who contributed to the success of our #NeurIPS23 Workshop! To our authors, reviewers, speakers, attendees, advisors, and especially to our workshop organizers! Kelly Buchanan Rui Yang Fan Feng Andreas Kriegler Yubin Xie @ianxmason Tobias Uelwer

🚨The Amsterdam Machine learning group UvA AMLab is hiring 2 PhDs on #AI4Fintech in collaboration with Adyen 🚨 - 1 PhD on #causalML with Sara Magliacane (she/her) - hiring 2 PhD students - 1 PhD on #RL with Herke van Hoof Deadline: **11 March 2024** Details: vacatures.uva.nl/UvA/job/2-PhD-…

Announcing the Reinforcement Learning Beyond Rewards workshop at the first RL_Conference. Think that rewards aren't enough for RL? Working on RLHF? Thinking of alternative ways of alignment? Creating a foundational model for RL? or have ideas on task-agnostic RL algo? Join us

The submission deadline for RL Beyond Rewards RL_Conference is approaching fast in 10 days (3rd May 11:59 AOE). The submission link is open here: openreview.net/group?id=rl-co…

⚠️ Final call for submitting your ideas on RL beyond Rewards at the Reinforcement Learning Conference RL_Conference! Check out our earlier posts for more info and call for papers.

The main issues with the RL framework are the low information content of the reward signal, the task-specificity / lack of generality of reward signals, and the question where reward comes from in the first place (especially for abstract goals where recognizing success itself

It is officially less than a week before the workshop begins⌛️ The workshop schedule is posted here: rlbrew-workshop.github.io/schedule.html A complete list of accepted papers can be found here: rlbrew-workshop.github.io/papers.html

🥳RLBReW Social🥳 @ RLC (RL_Conference ) Socials are 🧡 of any conference. We invite you to join us on the evening of August 9 to discuss wacky RL ideas, and find friends and collaborators! RSVP here: lu.ma/500nd7gj

RLBReW@RLC workshop talks are now live for everyone to watch 👇. We had a large participation, and this wouldn't have been possible without our organizers Caleb Chuck, Siddhant Agarwal Harshit Sikchi Gokul Swamy Fan Feng Yuchen Cui Akanksha Saran Joey Hejna Roberta Raileanu

Super excited to announce our Causal-Copilot: an LLM-driven toolkit for automatic causal analysis! Gain precise insights effortlessly, without requiring deep expertise in causality!😀

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New PhD position at UvA AMLab on learning concepts with theoretical guarantees using #causality and #RL with me, Frans Oliehoek (TU Delft) and Herke van Hoof 💥 Deadline: 15 June werkenbij.uva.nl/en/vacancies/p…

🏹 Job alert: PhD Position on Learning Concepts with Theoretical Guarantees Using Causality and RL in Amsterdam Join UvA AMLab and cooperate with TU Delft. 📍 Amsterdam 🇳🇱 📅 Apply by: June 15th bit.ly/3SfkNQP