7 papers
Geometric Stability: The Missing Axis of Representations
Prashant C. Raju
Representational similarity analysis and related methods compare the internal geometries of neural networks, but they measure only alignment between spaces, leaving a blind spot --…
Geometric Stability of Neural Population Codes: Regional Variation, Behavioral Relevance, and Circuit Dependence
Prashant C. Raju
Current models of representational reliability in neural populations focus on temporal stability: whether population centroids are preserved across sessions and days. This framing…
Geometric coherence of single-cell CRISPR perturbations reveals regulatory architecture and predicts cellular stress
Prashant C. Raju
Genome engineering has achieved sequence-level precision, yet predicting the transcriptomic state a cell will occupy after perturbation remains open. Single-cell CRISPR screens mea…
Geometric Phase Transition Enables Extreme Hippocampal Memory Capacity
Prashant C. Raju
Memory systems can store vastly different amounts of information despite similar hardware constraints. Here, we show that superior spatial memory emerges from a discrete stiffening…
The Geometric Canary: Predicting Steerability and Detecting Drift via Representational Stability
Prashant C. Raju
Reliable deployment of language models requires two capabilities that appear distinct but share a common geometric foundation: predicting whether a model will accept targeted behav…
From Syntax to Semantics: Geometric Stability as the Missing Axis of Perturbation Biology
Prashant C. Raju
The capacity to precisely edit genomes has outpaced our ability to predict the consequences. A cell can be genetically perfect and therapeutically useless: edited exactly as intend…