🚨We propose EquiReg, a generalized regularization framework that uses symmetry in generative diffusion models to improve solutions to inverse problems. arxiv.org/abs/2505.22973

@aditijc.bsky.social, Rayhan Zirvi, Abbas Mammadov, @jiacheny.bsky.social, Chuwei Wang, @anima-anandkumar.bsky.social 1/

I am joining @ualberta.bsky.social as a faculty member and
@amiithinks.bsky.social!

My research group is recruiting MSc and PhD students at the University of Alberta in Canada. Research topics include generative modeling, representation learning, interpretability, inverse problems, and neuroAI.

We have released VARS-fUSI: Variable sampling for fast and efficient functional ultrasound imaging (fUSI) using neural operators.

The first deep learning fUSI method to allow for different sampling durations and rates during training and inference. biorxiv.org/content/10.1... 1/

Rayhan Zirvi is presenting our paper "Diffusion State-Guided Projected Gradient for Inverse Problems" at #ICLR2025! Joint work with @anima-anandkumar.bsky.social 1/

paper: openreview.net/pdf?id=kRBQw...
code: github.com/Anima-Lab/Di...
website: diffstategrad.github.io

Blog post by Demba Ba, @saramatias.bsky.social and @btolooshams.bsky.social on our recent @cp-neuron.bsky.social paper proposing a new deconvolutional method based on algorithm unrolling to anlayze neural data across recording modalities

How does the brain integrate prior knowledge with sensory data to perceive the world?

Come check out our poster [1-090] at #cosyne2025:
"A feedback mechanism in generative networks to remove visual degradation," joint work with Yuelin Shi, @anima-anandkumar.bsky.social, and Doris Tsao. 1/2

How can we design human-interpretable AI models to explain why neurons behave as they do?

Excited to share our work in collaboration with @saramatias.bsky.social, Hao Wu, Simona Temereanca, @naoshigeuchida.bsky.social, @neurovenki.bsky.social, @paulmasset.bsky.social, and Demba Ba @harvard.edu 1/21

New Deep Learning Framework Reveals Hidden Structure in Neural Activity 🧠 #neuro #science
www.mcb.harvard.edu/department/n... @naoshigeuchida.bsky.social @saramatias.bsky.social @neurovenki.bsky.social @btolooshams.bsky.social @kempnerinstitute.bsky.social @harvardbrainsci.bsky.social

Join us remotely or in person to hear from @ninamiolane.bsky.social and @louisacornelis.bsky.social on Geometric Intelligence in Minds and Mahcines.

Thanks, @mathildepapillon.bsky.social, for hosting!

Rayhan and I are presenting today our work on "Diffusion-State Guided Projected Gradient for Inverse Problems." at the D3S3 Workshop. Joint work with Dr. Anima Anandkumar #AInScience #NeurIPS2024 [1/6]

Paper: arxiv.org/abs/2410.03463

We welcome our next Keynote speaker, Ilker Yildirim, who is discussing "Reverse-engineering cognitive and neural representations with multilevel computational theories"!

Find us at the West Ballroom C!

Join us for our next Keynote invited talk from Stefanie Jegelka on "In-context Symmetries via Contextual World Models"!

Our first contributed talk is from @ccrommel.bsky.social on "ManiPose: Manifold-Constrained Multi-Hypothesis 3D Human Pose Estimation".

Eero Simoncelli on the geometry of the distribution of natural images

Ready for #NeurReps2024?

Our schedule at @neuripsconf.bsky.social
is out 📅
neurips.cc/virtual/2024...

Join us this Saturday! 🧠

With @eerosim.bsky.social @taliakonkle.bsky.social Stefanie Jegelka, Srinivas Turaga, Ilker Yildirim and Savannah Thais

I am giving a talk on "Sparse autoencoders for gaining mechanistic interpretability of neural signals" this Friday at the Catelch Chen Institute for Neuroscience. This is part of the workshop on AI for Neuro: How modern AI technologies enable advances in Neuroscience.