V3.2, a family of open-source reasoning and agentic AI models. The high compute version, DeepSeek-V3.2-Speciale, performs ...
This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
Abstract: This paper develops a Multi-Agent Deep Reinforcement Learning (MADRL) framework for underwater attack-defense scenarios with constrained sensing/communication. While maintaining balanced ...
Abstract: Over the past few years especially in the context of communication and information processing the importance of Natural language processing which demands efficient deep learning models has ...
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Where analytics meets innovation: Inside Ashutosh Agarwal’s transformational work
Ashutosh Agarwal is a specialist who connects analytics with practical strategy, who stands out in the era of digital ...
Overview: Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...
The new reinforcement learning system lets large language models challenge and improve themselves using real-world data instead of curated training sets. Meta researchers have unveiled a new ...
Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...
Introduction: Early diagnosis of Alzheimer's disease (AD) remains challenging due to the high similarity among AD, mild cognitive impairment (MCI), and cognitively normal (CN) individuals, as well as ...
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