Anirvan M. Sengupta

The paper introduces two biologically plausible algorithms for segmenting time series based on underlying dynamics, showing good performance on autoregressive models and voice recordings.

The paper investigates representational drift in neural networks, showing that noisy synaptic updates cause coordinated random walks in receptive fields while maintaining population code stability.

The paper shows that similarity-preserving neural networks develop localized receptive fields that tile manifolds, mirroring brain representations like place cells.

The paper investigates how nucleotide triphosphates (NTPs) and magnesium (Mg2+) affect gene expression in a cell-free system, finding that high NTP concentrations directly inhibit translation.