This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...

Abstract: Implicit neural representations (INRs) such as NeRF and SIREN encode a signal in neural network parameters and show excellent results for signal reconstruction. Using INRs for downstream ...

Fulfilment services startup QuickShift has raised INR 22 Cr ($2.5 Mn) in a Pre-Series A round led by Atomic Capital, with participation from Axilor Ventures and a few other unnamed investors. The ...

Abstract: Optimizing the performance of deep neural networks (DNNs) remains a significant challenge due to the sensitivity of models to both hyperparameter selection and weight initialization.

In cellular automata, simple rules create elaborate structures. Now researchers can start with the structures and reverse-engineer the rules. Alexander Mordvintsev showed me two clumps of pixels on ...

E2E Networks has received a contract letter from IndiaAI Mission to provide GPU resources worth INR 177 Cr to Gnani.ai E2E Networks will be allocating H100 SXM and H200 SXM GPU resources to the ...

in this video, we will understand what is Recurrent Neural Network in Deep Learning. Recurrent Neural Network in Deep Learning is a model that is used for Natural Language Processing tasks. It can be ...

What is CNN in Deep Learning? In this video, we understand what is CNN in Deep Learning and why do we need it. CNN (or Convolutional Neural Network) is the building block of all Computer Vision ...

ABSTRACT: To address the challenges of morphological irregularity and boundary ambiguity in colorectal polyp image segmentation, we propose a Dual-Decoder Pyramid Vision Transformer Network (DDPVT-Net ...