eLife

Distinct sensorimotor encoding in tuft dendrites and somata associated with action, correction, and learning

This important study reveals distinct representations of task-related information in the dendrites and somata of cortical neurons during sensorimotor learning and behavioral adaptation. The evidence ...

Context compression finally works in production: new research cuts LLM input 16x without the accuracy hit

LCLMs compress LLM context before decode — 8.8x faster at 16x compression, beating every KV cache method tested. Open-sourced by NYU and Columbia.
IEEE

Deriving Good LDPC Convolutional Codes from LDPC Block Codes

Abstract: Low-density parity-check (LDPC) convolutional codes are capable of achieving excellent performance with low encoding and decoding complexity. In this paper, we discuss several ...
IEEE

Woven convolutional codes .I. Encoder properties

Abstract: Encoders for convolutional codes with large free distances can be constructed by combining several less powerful convolutional encoders. This paper is devoted to constructions in which the ...
Frontiers

DLBWE-Cys: a deep-learning-based tool for identifying cysteine S-carboxyethylation sites using binary-weight encoding

Cysteine S-carboxyethylation, a novel post-translational modification (PTM), plays a critical role in the pathogenesis of autoimmune diseases, particularly ankylosing spondylitis. Accurate ...
GitHub

Blind Nonlinear Unmixing for Intimate Mixtures Using Hapke Model and Convolutional Neural Network

If you use this code and/or our simulated datasets please do not forget cite the following paper: B. Rasti, B. Koirala, and P. Scheunders, "HapkeCNN: Blind Nonlinear Unmixing for Intimate Mixtures ...
GitHub

MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing

If you use this code and/or our simulated datasets please do not forget cite the following paper: B. Rasti, B. Koirala, P. Scheunders and J. Chanussot, "MiSiCNet: Minimum Simplex Convolutional Network ...
Europe PMC

Systematic Encoding and Shortening of PAC Codes.

Polarization adjusted convolutional (PAC) codes are a class of codes that combine channel polarization with convolutional coding. PAC codes are of interest for their high performance. This paper ...