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Interpretability

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…It also considers interpretability, robustness and responsible deployment. The programme combines keynotes, research presentations and a discussion of the gap between architectural ideas and real-world systems. Workshop W05 runs from 08:30 to 12:00 local time. Paper submissions closed on 20 August and camera-rea

Thu, Nov 12, 2026

Workshop · Artificial Intelligence

…engineering still faces problems of interpretability, uncertainty and connections between molecular and system-level behaviour. Applied mathematicians, learning researchers and synthetic biologists will explore statistical methods for complex biological data, models that expose mechanisms, stochastic descriptions of noisy systems, multiscale modelling from molecules to populations and robust optimization for design under uncertainty. The workshop aims to develop mathematical foundations for more depend

Jul 11–16, 2027

Workshop · Mathematical Biology

…from 2 to 13 August 2027, focuses on interpretability in reasoning and mathematical cognition: how children or artificial systems use and acquire mathematical concepts, how mathematical intuition and expertise develop and interact, and how studying the heuristics and abstrac

Aug 2–13, 2027

Workshop · Cognition

SQI Seminar Series: Tal Linzen, NYU

Tal Linzen · New York University; Google

…post-training, evaluation, and interpretability.

Tue, Sep 15, 2026 · 20:00 UTC

Seminar · Computational Linguistics

…models, learning across data types, interpretability, generative modelling and translating algorithms into biological insight. The official event page retains the programme and speaker information. This event has ended; registration and abstract submission are closed.

Mar 10–13, 2026

Conference · Artificial Intelligence

Probing neural population dynamics with recurrent neural networks

Chethan Pandarinath · Emory University and Georgia Tech

Large-scale recordings of neural activity are providing new opportunities to study network-level dynamics with unprecedented detail. However, the sheer volume of data and its dynamical complexity are major barriers to uncovering and interpreting these dynamics. I will present latent factor analysis via dynamical systems, a sequential autoencoding approach that enables inference of dynamics from neuronal population spiking activity on single trials and millisecond timescales. I will also discuss recent adaptations of the method to uncover dynamics from neural activity recorded via 2P Calcium im

Wed, Jun 12, 2024 · 13:00 UTC

Seminar · Computational Neuroscience