Devendra Singh Dhami's Avatar

Devendra Singh Dhami

@devendradhami

Pahadi ๐Ÿ‡ฎ๐Ÿ‡ณ| Assistant Professor at TU Eindhoven ๐Ÿ‡ณ๐Ÿ‡ฑ| Causality, Neuro-symbolic AI, Probabilistic Circuits and pretty much all of Machine Learning ;)

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27.11.2024
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Latest posts by Devendra Singh Dhami @devendradhami

Excited to share that our paper "Synthesizing Visual Concepts as Vision-Language Programs" has been accepted to #CVPR2026! ๐ŸŽ‰

We propose a novel method that combines VLMs with symbolic program synthesis to learn reliable programs of visual concepts.

๐ŸŒ ml-research.github.io/vision-langu...

25.02.2026 21:05 ๐Ÿ‘ 3 ๐Ÿ” 2 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 0

An amazing conference at an amazing location. Mark your calendars for #UAI2026

16.12.2025 18:16 ๐Ÿ‘ 3 ๐Ÿ” 0 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0

A fantastic opportunity to join us in #Amsterdam for some hardcore #uncertainty in #AI ๐Ÿฆพ๐Ÿšฒ๐ŸŒทโœ–๏ธโœ–๏ธโœ–๏ธ

#causality #tractable #probabilistic #models #neurosymbolic #imprecise #probabilities #statistical #methods and more

16.12.2025 17:32 ๐Ÿ‘ 24 ๐Ÿ” 10 ๐Ÿ’ฌ 2 ๐Ÿ“Œ 1

Our poster, โ€œWhen Causal Dynamics Matter: Adapting Causal Strategies through Meta-Aware Interventionsโ€ will be presented during the second poster session of today, #2513 at #NeurIPS2025 .

Looking forward to the discussions!

05.12.2025 17:16 ๐Ÿ‘ 4 ๐Ÿ” 2 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0
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๐Ÿš€ 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 โ€œReasonable AI."

Apply now and make an impact where AI meets society.
๐Ÿ‘‰ buff.ly/bIvq7Mb

08.11.2025 14:29 ๐Ÿ‘ 8 ๐Ÿ” 6 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 2
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๐Ÿšจ 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.

30.11.2025 01:32 ๐Ÿ‘ 15 ๐Ÿ” 7 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 2
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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

04.11.2025 12:06 ๐Ÿ‘ 6 ๐Ÿ” 2 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 1

Same for me and also got 2 resubmissions from my NeurIPS batch ๐Ÿ™‚

29.09.2025 09:38 ๐Ÿ‘ 2 ๐Ÿ” 0 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0
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EurIPS is coming! ๐Ÿ“ฃ Mark your calendar for Dec. 2-7, 2025 in Copenhagen ๐Ÿ“…

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

16.07.2025 22:00 ๐Ÿ‘ 143 ๐Ÿ” 70 ๐Ÿ’ฌ 2 ๐Ÿ“Œ 19
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eurips.cc A NeurIPS-endorsed conference in Europe held in Copenhagen, Denmark

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

16.07.2025 22:05 ๐Ÿ‘ 124 ๐Ÿ” 38 ๐Ÿ’ฌ 2 ๐Ÿ“Œ 3

As I currently work with him, I can say with certainty that Cassio is in the middle

03.07.2025 08:16 ๐Ÿ‘ 2 ๐Ÿ” 0 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0

next is Elias Bareinboim (causalai.net) from Columbia University, who will discuss in his keynote talk about the recent

โœจ progress toward building causally intelligent AI systems โœจ

full abstract ๐Ÿ‘‰ www.auai.org/uai2025/keyn...

30.06.2025 09:34 ๐Ÿ‘ 9 ๐Ÿ” 4 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0
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time to announce our amazing keynote speakers!

we start with Francesca Dominici (hsph.harvard.edu/research/dom...) from Harvard University, who will talk about:

โœจ AI's uncertain, double-edged role in the fight against climate change โœจ

full abstract ๐Ÿ‘‰ www.auai.org/uai2025/keyn...

30.06.2025 09:28 ๐Ÿ‘ 11 ๐Ÿ” 4 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 1

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 ๐Ÿšฒ๐ŸŒท๐Ÿ‡ณ๐Ÿ‡ฑ

Deadline: June 15

03.06.2025 09:37 ๐Ÿ‘ 17 ๐Ÿ” 5 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0
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Uncertainty in Artificial Intelligence

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

๐Ÿ‘‰ www.auai.org/uai2025/tuto...

04.06.2025 09:25 ๐Ÿ‘ 14 ๐Ÿ” 5 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0
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Horizontal, vertical, hybrid data partitioning: heterogeneity is tough to handle in federated learning!

๐Ÿ”ฅIn โ€œScaling Probabilistic Circuits via Data Partitioning" - accepted at #UAI25 - we unify the different settings through aggregation of learned client distributions: arxiv.org/abs/2503.08141

08.05.2025 07:19 ๐Ÿ‘ 7 ๐Ÿ” 4 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0
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Excited to share that our paper got accepted at #ICML2025!! ๐ŸŽ‰

We challenge Vision-Language Models like OpenAIโ€™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 ๐Ÿ‘‡

02.05.2025 07:47 ๐Ÿ‘ 25 ๐Ÿ” 10 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 1
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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.

17.04.2025 17:56 ๐Ÿ‘ 15 ๐Ÿ” 5 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 0
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the #TPM โšกTractable Probabilistic Modeling โšกWorkshop is back at @auai.org #UAI2025!

Submit your works on:

- fast and #reliable inference
- #circuits and #tensor #networks
- normalizing #flows
- scaling #NeSy #AI
...& more!

๐Ÿ•“ deadline: 23/05/25
๐Ÿ‘‰ tractable-probabilistic-modeling.github.io/tpm2025/

16.04.2025 08:40 ๐Ÿ‘ 38 ๐Ÿ” 19 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 3

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.

05.04.2025 10:19 ๐Ÿ‘ 0 ๐Ÿ” 0 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 0

Well that is also true. ๐Ÿ˜

05.04.2025 07:36 ๐Ÿ‘ 0 ๐Ÿ” 0 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 0

A nice idea would be to have the acknowledgement along with some sort of justification

05.04.2025 07:31 ๐Ÿ‘ 1 ๐Ÿ” 0 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 0

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

05.04.2025 07:30 ๐Ÿ‘ 0 ๐Ÿ” 0 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 0

Yes but at least they had to write something on their own and we could engage with them.

05.04.2025 07:04 ๐Ÿ‘ 0 ๐Ÿ” 0 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 0

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!!

05.04.2025 02:17 ๐Ÿ‘ 1 ๐Ÿ” 0 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 0
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Exploring Neural Granger Causality with xLSTMs: Unveiling Temporal Dependencies in Complex Data Causality in time series can be difficult to determine, especially in the presence of non-linear dependencies. The concept of Granger causality helps analyze potential relationships between variables,...

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."

17.02.2025 06:18 ๐Ÿ‘ 15 ๐Ÿ” 3 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0

Congratulations!! This is an amazing work

12.02.2025 07:31 ๐Ÿ‘ 2 ๐Ÿ” 0 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 0
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BlendRL: A Framework for Merging Symbolic and Neural Policy Learning Humans can leverage both symbolic reasoning and intuitive reactions. In contrast, reinforcement learning policies are typically encoded in either opaque systems like neural networks or symbolicโ€ฆ

Thrilled to introduce BlendRLโ€” our neuro-symbolic RL that bridges intuitive & symbolic reasoning! ๐Ÿง ๐Ÿค– A step closer to reasoning agents that think & act seamlessly. ๐Ÿš€ Check out the details in our #ICLR2025 paper! #AI #ReinforcementLearning

24.01.2025 22:10 ๐Ÿ‘ 17 ๐Ÿ” 2 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0
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Thrilled to share our #ICLR2025 work on Meta-Causal States! ๐ŸŒŸ Causal graphs evolve with dynamic systems & agent actions. We show how to cluster causal models by qualitative behavior, revealing hidden dynamics & emergent relationships ๐Ÿš€ #Causality #ML

https://arxiv.org/abs/2410.13054

24.01.2025 19:34 ๐Ÿ‘ 12 ๐Ÿ” 6 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0

Very interesting!! Sorry won't be able to make it to the poster but will definitely look at the work in more detail

14.12.2024 01:29 ๐Ÿ‘ 2 ๐Ÿ” 0 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 0