🚨 Opportunity for #Neurosymbolic AI folks!
I’m looking for a PhD student or postdoc to join the 🇦🇹 FWF Cluster of Excellence Bilateral AI (think #NeSy++):
www.bilateral-ai.net
Feel free to reach out or share 🙌
Excited to share that our paper "Synthesizing Visual Concepts as Vision-Language Programs" has been accepted to #CVPR2026! 🎉
We propose a novel method that combines VLMs with symbolic program synthesis to learn reliable programs of visual concepts.
🌐 ml-research.github.io/vision-langu...
An amazing conference at an amazing location. Mark your calendars for #UAI2026
A fantastic opportunity to join us in #Amsterdam for some hardcore #uncertainty in #AI 🦾🚲🌷✖️✖️✖️
#causality #tractable #probabilistic #models #neurosymbolic #imprecise #probabilities #statistical #methods and more
Our poster, “When Causal Dynamics Matter: Adapting Causal Strategies through Meta-Aware Interventions” will be presented during the second poster session of today, #2513 at #NeurIPS2025 .
Looking forward to the discussions!
🚀 Join @tuda.bsky.social and @hessianai.bsky.social as Professor for Ethical & Safe AI to advance the algorithmic foundations of ethical and safe AI and to shape “Reasonable AI."
Apply now and make an impact where AI meets society.
👉 buff.ly/bIvq7Mb
🚨 New paper alert!
We introduce Vision-Language Programs (VLP), a neuro-symbolic framework that combines the perceptual power of VLMs with program synthesis for robust visual reasoning.
I'm excited to share some updates:
1) Our paper "When Causal Dynamics Matter: Adapting Causal Strategies through Meta-Aware Interventions" (openreview.net/pdf?id=3fpYX...) will be at #NeurIPS2025
We introduce Meta-Causal Analysis to model qualitative transitions of causal systems. 1/4
Same for me and also got 2 resubmissions from my NeurIPS batch 🙂
EurIPS is coming! 📣 Mark your calendar for Dec. 2-7, 2025 in Copenhagen 📅
EurIPS is a community-organized conference where you can present accepted NeurIPS 2025 papers, endorsed by @neuripsconf.bsky.social and @nordicair.bsky.social and is co-developed by @ellis.eu
eurips.cc
NeurIPS is endorsing EurIPS, an independently-organized meeting which will offer researchers an opportunity to additionally present NeurIPS work in Europe concurrently with NeurIPS.
Read more in our blog post and on the EurIPS website:
blog.neurips.cc/2025/07/16/n...
eurips.cc
As I currently work with him, I can say with certainty that Cassio is in the middle
next is Elias Bareinboim (causalai.net) from Columbia University, who will discuss in his keynote talk about the recent
✨ progress toward building causally intelligent AI systems ✨
full abstract 👉 www.auai.org/uai2025/keyn...
time to announce our amazing keynote speakers!
we start with Francesca Dominici (hsph.harvard.edu/research/dom...) from Harvard University, who will talk about:
✨ AI's uncertain, double-edged role in the fight against climate change ✨
full abstract 👉 www.auai.org/uai2025/keyn...
Are you interested in improving the #interpretability, #robustness and #safety of current AI systems with #causality and #RL?
Apply to our PhD position in Amsterdam 🚲🌷🇳🇱
Deadline: June 15
did you check our amazing list of tutorials in Rio?
spanning
- hyperparameter optimization
- counterfactual reasoning
- bayesian nonparametrics for causality
- causal inference with deep generative models
- modern variational inference
👉 www.auai.org/uai2025/tuto...
Horizontal, vertical, hybrid data partitioning: heterogeneity is tough to handle in federated learning!
🔥In “Scaling Probabilistic Circuits via Data Partitioning" - accepted at #UAI25 - we unify the different settings through aggregation of learned client distributions: arxiv.org/abs/2503.08141
Excited to share that our paper got accepted at #ICML2025!! 🎉
We challenge Vision-Language Models like OpenAI’s o1 with Bongard problems, classic visual reasoning challenges and uncover surprising shortcomings.
Check out the paper: arxiv.org/abs/2410.19546
& read more below 👇
I'm excited to present our spotlight on meta-causal models at #ICLR2025 next week.
We model evolving causal graphs in dynamic systems. Applications to inference and attribution of agent actions. Paper: openreview.net/forum?id=J9V...
Visit our poster #441 during the Sat 3pm session.
the #TPM ⚡Tractable Probabilistic Modeling ⚡Workshop is back at @auai.org #UAI2025!
Submit your works on:
- fast and #reliable inference
- #circuits and #tensor #networks
- normalizing #flows
- scaling #NeSy #AI
...& more!
🕓 deadline: 23/05/25
👉 tractable-probabilistic-modeling.github.io/tpm2025/
In my experience a discussion works well. In a lot of my papers we were able to have a discussion with the reviewers and get our scores up. Many tines there was no change as well but I still prefer a nice discussion over a mere button click.
Well that is also true. 😁
A nice idea would be to have the acknowledgement along with some sort of justification
I know that. My point is that clicking a button is useless and most reviewers will not engage. In our case reviewers asked for experiments, we provide them and people just click the acknowledgement button without any accountability. As an AC, in my batch at least some reviewers are engaging
Yes but at least they had to write something on their own and we could engage with them.
Idea of having a rebuttal acknowledgement button in #ICML2025 is a big goof up. It reduces the accountability of the reviewers since we don't get anything even after answering everything. If it was a discussion then at least they are forced to say what they did or did not like!!
xLSTM for time series with Granger causality: arxiv.org/abs/2502.09981
xLSTM again shows superb performance at time series analysis.
"Our experimental evaluations on three datasets demonstrate the overall efficacy of our proposed GC-xLSTM model."
Congratulations!! This is an amazing work
Thrilled to introduce BlendRL— our neuro-symbolic RL that bridges intuitive & symbolic reasoning! 🧠🤖 A step closer to reasoning agents that think & act seamlessly. 🚀 Check out the details in our #ICLR2025 paper! #AI #ReinforcementLearning
Thrilled to share our #ICLR2025 work on Meta-Causal States! 🌟 Causal graphs evolve with dynamic systems & agent actions. We show how to cluster causal models by qualitative behavior, revealing hidden dynamics & emergent relationships 🚀 #Causality #ML
https://arxiv.org/abs/2410.13054