Come talk to Pari and me on Tuesday May 2 from 5:00-6:30 pm (Central Africa Time). We'll be happy to talk about anything related to doing research in industry, optimization, generalization, trustworthy AI, and related topics.

In our #ICML2023 work, Dmitry Krotov, Mohammed J Zaki, Parikshit Ram, and I uncover a novel connection between Dense Associative Memory dynamics and the inherent discrete assignment to propose an unconstrained continuous relaxation of the discrete clustering problem (ClAM).

K-means clustering requires non-differentiable cluster assignment. Deep clustering replaces discrete assignment with soft assignment (80% of the data point➡️cluster 1, 20%➡️cluster 2). This violates the fundamental premise of clustering – each point belongs to only one cluster.

I am excited to announce Associative Memory & Hopfield Networks Workshop NeurIPS Conference 2023! We have a stellar lineup of invited speakers. The call for contributed papers is now open. See you in New Orleans! Website: amhn.vizhub.ai Submission: openreview.net/group?id=NeurI…

Check out this amazing interactive demo of Associative Memory by Ben Hoover and Hendrik S (find me in blueksy) 👏👏 There is also a mathematical explanation of the underlying mechanics amhn.vizhub.ai/demo/#demo-ana…

Don't miss the golden opportunity to attend 𝐍𝐞𝐮𝐫𝐨-𝐒𝐲𝐦𝐛𝐨𝐥𝐢𝐜 𝐀𝐈 𝐒𝐮𝐦𝐦𝐞𝐫 𝐒𝐜𝐡𝐨𝐨𝐥 2023 (𝐀𝐮𝐠𝐮𝐬𝐭 29-30). Register for free at: neurosymbolic.github.io/nsss2023/ #ai #neurosymbolicai #machinelearning #reasoning #knowledge #largelanguagemodels

The CfP for our NeurIPS Conference Workshop on Associative Memory & Hopfield Networks is out! The deadline is Sep 29th! Details: amhn.vizhub.ai/cfp/ Speakers: John Hopfield Dmitry Krotov Sepp Hochreiter Carlo Lucibello Krzysztof Choromanski FieteGroup MIT-IBM Watson AI Lab Harvard University IBM Research

Please consider submitting your best work to the NeurIPS workshop Associative Memory & Hopfield Networks in 2023! Memory-inspired architectures, energy based models, NeuroAI, and much more. Call for papers: amhn.vizhub.ai/cfp/ Deadline: October 6 amhn.vizhub.ai

Excited to share the schedule for our NeurIPS Conference AMHN workshop at #NeurIPS2023: amhn.vizhub.ai/#schedule Please consider submitting your latest & greatest (new work, NeurIPS, AAAI, ICLR, etc): CfP amhn.vizhub.ai/cfp Deadline Oct 6 (AoE) Submissions openreview.net/group?id=NeurI…

Diffusion models are uncannily similar to Associative Memories. Both “retrieve memories" from an initial signal by descending the energy gradient. Diffusion Models assume an energy. Associative Memories define it. See our new paper: Memory in Plain Sight arxiv.org/abs/2309.16750

There has been many discussions around Hopfield Networks of associative memory in the past couple of weeks. But what are the modern frontiers and recent developments in this field? If you want to learn more about this, please check out the NeurIPS 2023 workshop dedicated to this

It was a great honor to organize this workshop and have John Hopfield himself (and Dmitry Krotov ) share their thoughts and insights.

Last year's workshop was awesome -- I learned a ton. Definitely in my top-3 most interesting future directions for AI (totally unbiased... 😇). Highly recommend watching John Hopfield’s talk from the workshop👇 #AI #HopfieldNetworks youtube.com/watch?v=3OnjX-…

Excited to share Dense Associative Memory through the Lens of Random Features accepted to #NeurIPS2024🎉 DenseAMs need new weights for each stored pattern–hurting scalability. Kernel methods let us add memories without adding weights! Distributed memory for DenseAMs, unlocked🔓

I am super excited to announce the call for papers for the New Frontiers in Associative Memories workshop at ICLR 2025. New architectures and algorithms, memory-augmented LLMs, energy-based models, Hopfield networks, associative memory and diffusion, and many other exciting

What is Associative Memory and how can it be used in modern AI? 🔷 If I show you an image of a strawberry, can you remember what it smells like or tastes like? 🔷 Can you name a movie by seeing the emojis below? 🔷 Can you name the gentlemen in the picture without seeing

Ben Hoover, Parikshit Ram, Bao Pham, and I prepared a Tutorial on Associative Memory for ICML Conference, which we will present next week. (Hopefully) an approachable introduction to the field for the newcomers with hands-on notebooks and some suggested problem sets. In the next few days

There is obviously way more to Associative Memory than can fit in this thread On July 14 Dmitry Krotov Parikshit Ram and I will present a tutorial at #ICML2025 on what we've learned about AMs Join if you want to be convinced that AI needs physics to reach its full potential 🤙

Our recent preprint gives a gist of what we hope to cover 📜arxiv.org/abs/2507.06211 We also have an accompanying website with code examples. Still under construction 🙈. Will post updates over the next few days! 🖥️ tutorial.amemory.net With Dmitry Krotov Parikshit Ram Bao Pham

🚨 Excited to attend #ICML2025 and share our latest work (OPTML @MSU) on LLM unlearning -- think of it as AI surgery: removing harmful knowledge while preserving general utility. Catch us at: 🔹 [Paper 1] Tues, July 15 @ 4:30pm PT | E-1108 📄 Invariance Makes LLM Unlearning