Visual Studio Magazine

Support Vector Regression with SGD Training Using C#

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
C&EN

Normalized Protein–Ligand Distance Likelihood Score for End-to-End Blind Docking and Virtual Screening

Department of Chemistry, New York University, New York, New York 10003, United States Department of Chemistry, New York University, New York, New York 10003, United States Simons Center for ...
IEEE

A Low-Latency and Lightweight FPGA-Based Engine for Softmax and Layer Normalization Acceleration

Abstract: Vector operations such as GELU, softmax, and layer normalization are essential for transformers, but generally consume long latency on general-purpose CPU and GPU due to their low arithmetic ...
PNAS

Building transformers from neurons and astrocytes

Transformers have become the default choice of neural architecture for many machine learning applications. Their success across multiple domains such as language, vision, and speech raises the ...
Europe PMC

Exploring Representations for Singular and Multi-Concept Relations for Biomedical Named Entity Normalization.

Since the rise of the COVID-19 pandemic, peer-reviewed biomedical repositories have experienced a surge in chemical and disease related queries. These queries have a wide variety of naming conventions ...
GitHub

CellCall: Integrating paired ligand-receptor and transcription factor activities for cell-cell communication

2021/02/02 -- Increase the number of LR datasets reference to 1141. 2021/02/01 -- The reference LR datasets change to, core and extended, two parts. And rename the tool to CellCall. CellCall is a ...
IEEE

Class-Variant Margin Normalized Softmax Loss for Deep Face Recognition

Abstract: In deep face recognition, the commonly used softmax loss and its newly proposed variations are not yet sufficiently effective to handle the class imbalance and softmax saturation issues ...