964 citations · 1.9k across the 44 of their papers we have counts for
45 papers
AI without networks
Partha P Mitra, Clément Sire
Contemporary Artificial Intelligence (AI) stands on two legs: large training data corpora and many-parameter artificial neural networks (ANNs). The data corpora are needed to repre…
Fitting Elephants
Partha P Mitra
Textbook wisdom advocates for smooth function fits and implies that interpolation of noisy data should lead to poor generalization. A related heuristic is that fitting parameters s…
Detection and skeletonization of single neurons and tracer injections using topological methods
Dingkang Wang, Lucas Magee, Bing-Xing Huo +8
Neuroscientific data analysis has traditionally relied on linear algebra and stochastic process theory. However, the tree-like shapes of neurons cannot be described easily as point…
Understanding overfitting peaks in generalization error: Analytical risk curves for and penalized interpolation
Partha P Mitra
Traditionally in regression one minimizes the number of fitting parameters or uses smoothing/regularization to trade training (TE) and generalization error (GE). Driving TE to zero…
SSFN -- Self Size-estimating Feed-forward Network with Low Complexity, Limited Need for Human Intervention, and Consistent Behaviour across Trials
Saikat Chatterjee, Alireza M. Javid, Mostafa Sadeghi +4
We design a self size-estimating feed-forward network (SSFN) using a joint optimization approach for estimation of number of layers, number of nodes and learning of weight matrices…
Estimating Diffeomorphic Mappings between Templates and Noisy Data: Variance Bounds on the Estimated Canonical Volume Form
Daniel J. Tward, Partha Mitra, Michael I. Miller
Anatomy is undergoing a renaissance driven by availability of large digital data sets generated by light microscopy. A central computational task is to map individual data volumes…