Majdi Hassan
@majdi_has
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PhD student @ Mila | ML for chemistry and biophysics
Joined April 2022
(1/n)🚨You can train a model solving DFT for any geometry almost without training data!🚨. Introducing Self-Refining Training for Amortized Density Functional Theory — a variational framework for learning a DFT solver that predicts the ground-state solutions for different
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RT @leoeleoleo1: Wrote up some notes providing an introduction to discrete diffusion models, going into the theory of time-inhomogeneous CT….
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RT @martoskreto: AI4Mat is back for NeurIPS! time to crystallize those ideas and make a solid-state submission by august 22, 2025 💪. new th….
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RT @lavoiems: 🧵 Everyone is chasing new diffusion models—but what about the representations they model from?.We introduce Discrete Latent C….
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RT @danyalrehman17: Wrapping up #ICML2025 on a high note — thrilled (and pleasantly surprised!) to win the Best Paper Award at @genbio_work….
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RT @AlexanderTong7: Come check out SBG happening now! W-115 11-1:30 with.@charliebtan .@bose_joey .Chen Lin.@leonklein26 .@mmbronstein http….
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RT @martoskreto: we’re not kfc but come watch us cook with our feynman-kac correctors, 4:30 pm today (july 16) at @icmlconf poster session….
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RT @bose_joey: 👋 I'm at #ICML2025 this week, presenting several papers throughout the week with my awesome collaborators! . Please do reach….
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RT @nmboffi: 🧵generative models are sweet, but navigating existing repositories can be overwhelming, particularly when starting a new resea….
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RT @k_neklyudov: 1/ Where do Probabilistic Models, Sampling, Deep Learning, and Natural Sciences meet? 🤔 The workshop we’re organizing at #….
fpineurips.framer.website
FPI Workshop
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RT @k_neklyudov: (1/n) Sampling from the Boltzmann density better than Molecular Dynamics (MD)? It is possible with PITA 🫓 Progressive Infe….
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RT @vdbergrianne: 🚀 After two+ years of intense research, we’re thrilled to introduce Skala — a scalable deep learning density functional t….
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RT @AlexanderTong7: Check out FKCs! A principled flexible approach for diffusion sampling. I was surprised how well it scaled to high dimen….
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RT @k_neklyudov: Why do we keep sampling from the same distribution the model was trained on?. We rethink this old paradigm by introducing….
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RT @martoskreto: 🧵(1/6) Delighted to share our @icmlconf 2025 spotlight paper: the Feynman-Kac Correctors (FKCs) in Diffusion. Picture this….
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RT @JiajunHe614: [1/9]🚀Excited to share our new work, RNE! A plug-and-play framework for everything about diffusion model density and contr….
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RT @acceleration_c: We're spotlighting #WomenInSTEM and their inspiring journeys! Meet @martoskreto, Computer Science PhD student @UofT. V….
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RT @emilianopp_: Excited that our paper "Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization" was a….
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Seems like I forgot to link the paper 😅. Paper:
arxiv.org
Density Functional Theory (DFT) allows for predicting all the chemical and physical properties of molecular systems from first principles by finding an approximate solution to the many-body...
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(8/n)⚡ Runtime efficiency. Self-refining training reduces total runtime up to 4 times compared to the baseline .and up to 2 times compared to the fully-supervised approach!!!.Less need for large pre-generated datasets — training and sampling happen in parallel.
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