In cooking, execution is more important than the dish itself, even for simple dishes. Hummus can be great or terrible. The same is true of scientific ideas. Almost nothing works as we wish at first. Persistence, high standards, and attention to detail make all the difference.

Our accepted ICML paper on prototype-based Concept Bottleneck Models is now on arXiv! We introduce Prototype-Grounded Concept Models (PGCMs), enabling verifiable concept alignment through interpretable visual prototypes 🔍🧠. Check it out at: arxiv.org/abs/2604.16076

1/5 Tomorrow I’ll talk about the 𝐩𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐬𝐭𝐢𝐜 𝐩𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐬𝐞𝐦𝐚𝐧𝐭𝐢𝐜𝐬 𝐨𝐟 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭𝐢𝐚𝐛𝐥𝐞 𝐩𝐫𝐨𝐯𝐢𝐧𝐠 at #NeurIPS San Diego (poster #614 11am). 📃 openreview.net/pdf?id=rEUbD... 📺 www.youtube.com/watch?v=sOTX...

Scholar Inbox for NeurIPS is live now.

Eugene Vinitsky 🍒@eugenevinitsky.bsky.social · 8mo ago

Any word on a NeurIPS scholar inbox? It was so useful for ICML

Terence Tao (@teorth.bsky.social) has written a thread on Mastodon about the impact of the federal grant freeze to UCLA, particularly to his own field of Mathematics. UCLA's IPAM (Institute of Pure and Applied Mathematics) could shut down entirely mathstodon.xyz/@tao/1149568...

We’re proud to announce the launch of AutumnBench, an open-source benchmark developed on our Autumn platform. This benchmark, led by our MARA team, provides a novel platform for evaluating world modeling and causal reasoning in both human and artificial intelligence.

The crazy thing about epicycles: at the time Kopernicus introduced his model they were far superior in terms of predictive power compared to the heliocentric model. This was still true when Kepler refined the model with ellipses. Epicycles had been extremely refined over time (capital+labor)

We propose Neurosymbolic Diffusion Models! We find diffusion is especially compelling for neurosymbolic approaches, combining powerful multimodal understanding with symbolic reasoning 🚀 Read more 👇

Just under 10 days left to submit your latest endeavours in #tractable probabilistic models! Join us at TPM @auai.org #UAI2025 and show how to build #neurosymbolic / #probabilistic AI that is both fast and trustworthy!

antonio vergari ⚔️ short-circuiting@nolovedeeplearning.bsky.social · last yr.

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/

We developed a library to make logical reasoning embarrasingly parallel on the GPU. For those at ICLR 🇸🇬: you can get the juicy details tomorrow (poster #414 at 15:00). Hope to see you there!

We all know backpropagation can calculate gradients, but it can do much more than that! Come to my #AAAI2025 oral tomorrow (11:45, Room 119B) to learn more.

Are you at AAAI in Philadelphia and interested about #tensor-factorizations or #circuits or even both? Then join us today at our tutorial: "From tensor factorizations to circuits (and back!)" Details and materials here april-tools.github.io/aaai25-tf-pc... Time 4:15pm - 6:00pm, Room 117

🔥 Can AI reason over time while following logical rules in relational domains? We will present Relational Neurosymbolic Markov Models (NeSy-MMs) next week at #AAAI2025! 🎉 📜 Paper: arxiv.org/pdf/2412.13023 💻 Code: github.com/ML-KULeuven/... 🧵⬇️

‪I'm visiting the StarAI lab of @guyvdb.bsky.social at UCLA for a couple of months starting this week. If you're around and want to have a chat let me know :)

Happy to see our work at TMLR! We systematically show the relationships between two apparently different fields: tensor factorizations and circuits, and how bridging the two enables us to exchange results, research opportunitie in ML, and practical implementation solutions.

TMLR Published Papers@tmlr-pub.bsky.social · last yr.

New #Featured Certification: What is the Relationship between Tensor Factorizations and Circuits (and How Can We Exploit it)? Lorenzo Loconte, Antonio Mari, Gennaro Gala et al. https://openreview.net/forum?id=Y7dRmpGiHj #tensorized #factorizations #tensor

We are hiring for PhD positions! I’m looking for people interested in exploring the intersection of learning and reasoning with applications to anomaly detection and sports. @dtai-kuleuven.bsky.social @wannesm.bsky.social www.kuleuven.be/personeel/jo...

Several PhD Positions in Artificial Intelligence at Computer Science KU Leuven

All positions are in the Machine Learning subgroup of the Section for Declarative Languages and Artificial Intelligence (DTAI), which is part of the Department of Computer Science at KU Leuven. The DT...

kuleuven.be

Unsure where to submit your next research paper to now that aideadlin.es is not updated anymore? And let’s be honest, is the location not as important as the conference itself? 🗺️ Check out my latest side-project: deadlines.pieter.ai

Computer Science Conference Deadlines Map

Interactive world map of Computer Science, AI, and ML conference deadlines

deadlines.pieter.ai

Are you interested in more scalable reasoning under uncertainty and attending NeurIPS? Then pass by our poster #3708 later today at 4.30pm! 🕟 We use recursive integer arithmetic to express combinatorial problems and add uncertainty. Inference can be massively accelerated with tensors and the FFT. 🚀

🚨 Interpretable AI often means sacrificing accuracy—but what if we could have both? Most interpretable AI models, like Concept Bottleneck Models, force us to trade accuracy for interpretability. But not anymore, due to Concept-Based Memory Reasoner (CMR)! #NeurIPS2024 (1/7)

@ropeharz.bsky.social forced me to do this starter pack on #tractable #probabilistic modeling and #reasoning in #AI and #ML please write below if you want to be added (and sorry if I did not find you from the beginning). go.bsky.app/DhVNyz5

Meet our researchers from the DTAI lab at KU Leuven! Using this starter pack, you can keep up with all the AI research from our PhD students, post-docs, professors and alumni 🦋

mixtures of circuit approximations of algorithms, I tell you! kernel methods in the space of (short, propositional) programs!! why memorize and interpolate answers when you can memorize and interpolate answer-producing procedures??

Laura@lauraruis.bsky.social · 2y ago

To my surprise, we find the opposite of what I thought when we started this project: The approach to reasoning LLMs use looks unlike retrieval, and more like a generalisable strategy synthesising procedural knowledge from many documents doing a similar form of reasoning.

Back in the days everyone wanted to be with the cool kids. Now everyone wants to be in a 🦋 starter pack. 🤣

Excited to share our #NeurIPS 2024 Oral, Convolutional Differentiable Logic Gate Networks, leading to a range of inference efficiency records, including inference in only 4 nanoseconds 🏎️. We reduce model sizes by factors of 29x-61x over the SOTA. Paper: arxiv.org/abs/2411.04732

I made a starter pack with the people doing something related to Neurosymbolic AI that I could find. Let me know if I missed you! go.bsky.app/RMJ8q3i