Jenelle Feather

Jenelle Feather

@jfeather.bsky.social

Assistant Professor in Neuroscience and Psychology at #CarnegieMellon. I study how humans and computers hear and see.

1.2K followers511 following51 posts

Jenelle Feather reposted

🚨 #CCN2026 Proceedings submissions are open! CCN 2026 again features an 8-page Proceedings track (alongside extended abstracts). Accepted papers will appear in CCN-Proceedings (CCN‑P) with DOIs on OpenReview.

Jenelle Feather reposted

arguably the most important component of AI for neuroscience: data, and its usability

Data on the Brain & Mind @NeurIPS2025@dataonbrainmind.bsky.social

🚨 Excited to announce our #NeurIPS2025 Workshop: Data on the Brain & Mind 📣 Call for: Findings (4- or 8-page) + Tutorials tracks 🎙️ Speakers include @dyamins.bsky.social @lauragwilliams.bsky.social @cpehlevan.bsky.social 🌐 Learn more: data-brain-mind.github.io

Join us at #NeurIPS2025 for our Data on the Brain & Mind workshop! We aim to connect machine learning researchers and neuroscientists/cognitive scientists, with a focus on emerging datasets. More info: data-brain-mind.github.io

Data on the Brain & Mind @NeurIPS2025@dataonbrainmind.bsky.social

🚨 Excited to announce our #NeurIPS2025 Workshop: Data on the Brain & Mind 📣 Call for: Findings (4- or 8-page) + Tutorials tracks 🎙️ Speakers include @dyamins.bsky.social @lauragwilliams.bsky.social @cpehlevan.bsky.social 🌐 Learn more: data-brain-mind.github.io

Jenelle Feather reposted

Jenelle Feather reposted

Consider submitting your recent work on stimulus synthesis and selection to our special issue at JOV!

Eero Simoncelli@eerosim.bsky.social

Submissions now accepted for a special issue of the Journal of Vision: Choose your stimuli wisely: Advances in stimulus synthesis and selection Submission deadline: Dec 12, 2025 Futher details: jov.arvojournals.org/ss/synthetic...

Topics include but are not limited to: •Optimal and adaptive stimulus selection for fitting, developing, testing or validating models •Stimulus ensembles for model comparison •Methods to generate stimuli with “naturalistic” properties •Experimental paradigms and results using model-optimized stimuli

Jenelle Feather reposted

What is the probability of an image? What do the highest and lowest probability images look like? Do natural images lie on a low-dimensional manifold? In a new preprint with Zahra Kadkhodaie and @eerosim.bsky.social, we develop a novel energy-based model in order to answer these questions: 🧵

Jenelle Feather reposted

Just a few months until Cognitive Computational Neuroscience comes to Amsterdam! Check out our now-complete schedule for #CCN2025, with descriptions of each of the Generative Adversarial Collaborations (GACs), Keynotes-and-Tutorials (K&Ts), Community Events, Keynote Speakers, and social activities!

CogCompNeuro@cogcompneuro.bsky.social

A detailed schedule for CCN2025 is available on our website now, including the specific keynotes / GACs / community events taking place: 2025.ccneuro.org/schedule-of-... The early bird registration deadline is coming up this Friday (23rd May)!

Jenelle Feather reposted

I’m happy to be at #VSS2025 and share what our lab has been up to this year! I’m also honored to receive this year’s young investigator award and will give a short talk at the awards ceremony Monday

We are presenting our work “Discriminating image representations with principal distortions” at #ICLR2025 today (4/24) at 3pm! If you are interested in comparing model representations with other models or human perception, stop by poster #63. Highlights in 🧵 openreview.net/forum?id=ugX...

openreview.netDiscriminating image representations with principal distortionsImage representations (artificial or biological) are often compared in terms of their global geometric structure; however, representations with similar global structure can have strikingly...
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These examples demonstrate how our framework can be used to probe for informative differences in local sensitivities between complex models, and suggest how it could be used to compare model representations with human perception.

We are presenting our work “Discriminating image representations with principal distortions” at #ICLR2025 today (4/24) at 3pm! If you are interested in comparing model representations with other models or human perception, stop by poster #63. Highlights in 🧵 openreview.net/forum?id=ugX...

openreview.netDiscriminating image representations with principal distortionsImage representations (artificial or biological) are often compared in terms of their global geometric structure; however, representations with similar global structure can have strikingly...
View full thread

As an example, we use this framework to compare a set of simple models of the early visual system, identifying a novel set of image distortions that allow immediate comparison of the models by visual inspection.

In a second example, we apply our method to a set of deep neural network models and reveal differences in the local geometry that arise due to architecture and training types, illustrating the method's potential for revealing interpretable differences between computational models.

We are presenting our work “Discriminating image representations with principal distortions” at #ICLR2025 today (4/24) at 3pm! If you are interested in comparing model representations with other models or human perception, stop by poster #63. Highlights in 🧵 openreview.net/forum?id=ugX...

openreview.netDiscriminating image representations with principal distortionsImage representations (artificial or biological) are often compared in terms of their global geometric structure; however, representations with similar global structure can have strikingly...
View full thread

We then extend this work to show that the metric may be used to optimally differentiate a set of *many* models, by finding a pair of “principal distortions” that maximize the variance of the models under this metric.

We are presenting our work “Discriminating image representations with principal distortions” at #ICLR2025 today (4/24) at 3pm! If you are interested in comparing model representations with other models or human perception, stop by poster #63. Highlights in 🧵 openreview.net/forum?id=ugX...

openreview.netDiscriminating image representations with principal distortionsImage representations (artificial or biological) are often compared in terms of their global geometric structure; however, representations with similar global structure can have strikingly...
View full thread

We propose a framework for comparing a set of image representations in terms of their local geometries. We quantify the local geometry of a representation using the Fisher information matrix (FIM), a standard statistical tool for characterizing the sensitivity to local stimulus distortions.

We use the FIM to define a metric on the local geometry of an image representation near a base image. This metric can be related to previous work investigating the sensitivities of one or two models.

We are presenting our work “Discriminating image representations with principal distortions” at #ICLR2025 today (4/24) at 3pm! If you are interested in comparing model representations with other models or human perception, stop by poster #63. Highlights in 🧵 openreview.net/forum?id=ugX...

openreview.netDiscriminating image representations with principal distortionsImage representations (artificial or biological) are often compared in terms of their global geometric structure; however, representations with similar global structure can have strikingly...

Recent work suggests that many models are converging to representations that are similar to each other and (maybe) to human perception. However, similarity often focuses on stimuli that are far apart in stimulus space. Even if global geometry is similar, the local geometry can be quite different.

Applications close TODAY (April 14) for the 2025 Flatiron Institute Junior Theoretical Neuroscience Workshop. All you need to apply is a CV and a 1 page abstract. 🧠🗽

Jenelle Feather@jfeather.bsky.social

Applications are open for the 2025 Flatiron Institute Junior Theoretical Neuroscience Workshop! A two-day workshop 7/10-7/11 in NYC for PhD students and postdocs. All travel paid. Apply by April 14th.🧠🗽🧑‍🔬http://jtnworkshop2025.flatironinstitute.org/ @flatironinstitute.org @simonsfoundation.org

Jenelle Feather reposted

📣 Grad students and postdocs in computational and theoretical neuroscience: please consider applying for the 2025 Flatiron Institute Junior Theoretical Neuroscience Workshop! All expenses are covered. Apply by April 14. jtnworkshop2025.flatironinstitute.org

jtnworkshop2025.flatironinstitute.orgJTN - 2025JTN - 2025
Jenelle Feather@jfeather.bsky.social

Applications are open for the 2025 Flatiron Institute Junior Theoretical Neuroscience Workshop! A two-day workshop 7/10-7/11 in NYC for PhD students and postdocs. All travel paid. Apply by April 14th.🧠🗽🧑‍🔬http://jtnworkshop2025.flatironinstitute.org/ @flatironinstitute.org @simonsfoundation.org

Already feeling #cosyne2025 withdrawal? Apply to the Flatiron Institute Junior Theoretical Neuroscience Workshop! Applications due April 14th jtnworkshop2025.flatironinstitute.org

jtnworkshop2025.flatironinstitute.orgJTN - 2025JTN - 2025
Jenelle Feather@jfeather.bsky.social

Applications are open for the 2025 Flatiron Institute Junior Theoretical Neuroscience Workshop! A two-day workshop 7/10-7/11 in NYC for PhD students and postdocs. All travel paid. Apply by April 14th.🧠🗽🧑‍🔬http://jtnworkshop2025.flatironinstitute.org/ @flatironinstitute.org @simonsfoundation.org

Jenelle Feather reposted

We're bringing together leading researchers from top institutions worldwide to Split, Croatia this summer. If you're passionate about brain-inspired AI, computational neuroscience, or fundamental mathematical principles driving intelligence, this conference is the place to be!

Teddy's project is one of the only clear examples we know of (so far) where modifying the *objective function* used for training a deep neural network systematically improves neural prediction of IT responses. Come chat at his poster this afternoon at #cosyne2025! (Poster 2-036)

Teddy Yerxa@tedyerxa.bsky.social

If you are at #cosyne2025 come check out my poster this afternoon! We demonstrate a case where objective function design can systematically improve neural predictivity in deep networks. [2-036] Contrastive-Equivariant Self-Supervised Learning Improves Alignment with Primate Visual Area IT

Jenelle Feather reposted

Image representations are often compared in terms of their global geometry. I'm excited to present work at #cosyne2025 that proposes a method for comparing image representations based on their *local* geometry. Poster: 8p tonight #1-112

We are presenting two exciting projects tonight at #Cosyne2025! 🧠🧑‍🔬 [1-032] Changes in tuning curves, not neural population covariance, improve category separability in the primate ventral visual pathway [1-112] Comparing image representations in terms of sensitivities to local distortions

Jenelle Feather reposted

After a great conference in Boston, CCN is going to take place in Amsterdam in 2025! To help the exchange of ideas between #neuroscience, cognitive science, and #AI, CCN will for the first time have full length paper submissions (alongside the established 2 pagers)! Info below👇 #NeuroAI #CompNeuro