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2,613 papers
This paper presents a novel algorithm for optimizing the structure of self-organizing neural networks (SONNs) through dynamic adjustment of connection strengths. Traditional SONNs often rely on manually defined layer configurations, which can be suboptimal and require significant tuning. Our proposed algorithm, termed...
This paper introduces a novel dynamic topology-based non-linear reinforcement learning (RL) algorithm designed to enhance learning efficiency and robustness. Traditional reinforcement learning methods often rely on static strategies, limiting adaptability and vulnerability to environmental changes. Our algorithm dynami...
This paper introduces a novel approach to dynamic program optimization leveraging multi-modal contextual information. The core idea is to combine code execution data, static code analysis, and natural language descriptions to enable adaptive and dynamic optimization strategies. We propose a deep learning-based framewor...
This paper introduces a novel prediction framework based on adaptive non-linear geometry models. Traditional predictive models often rely on fixed parameters, limiting their accuracy and efficiency. Our approach dynamically adjusts model parameters to capture the complex, non-linear relationships within the system bein...
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This paper presents a novel self-adaptive neural network architecture, termed Dynamic Adaptive Neural Network (DANN), designed to enhance model generalization. Traditional neural networks often suffer from suboptimal performance due to fixed parameters and lack of adaptability. DANN leverages dynamic adjustments to bot...
This dataset provides experimental quasi-static axial compression data for 30 avian bone-inspired structures (ABIS) fabricated by fused deposition modeling (FDM) from carbon-fiber-reinforced polylactic acid (PLA-CF). Each specimen combines a tapered hollow tube with gyroid internal reinforcement. The configurations wer...
Source code, trained reinforcement-learning checkpoints, scenario configurations, raw experimental results, real USRP N210 hardware sensing data, and the compiled manuscript supporting the paper "ChainRadioNet-AI: A Multi-Seed Benchmark of Reinforcement Learning for Dynamic Spectrum Access."
This article examines the application of artificial intelligence technologies for optimizing energy consumption in smart residential complexes. The study analyzes contemporary approaches to implementing machine learning algorithms, neural networks, and predictive analytics for managing energy resources in multi-apartme...
Psychiatric disorders are complex, multidimensional pathologies rooted in various cognitive processes. Computational psychiatry aims to reveal distortions in these processes through behavior modeling, providing a deeper understanding of psychiatric disorders. Previous studies that used Daw's two-stage task linked imbal...
Habits develop as motivated behaviors that are strengthened by extended experience and feedback. While the performance component of a habit is relatively well studied, being linked to action-related neural dynamics in the basal ganglia and beyond, neural mechanisms for outcome feedback during habit formation, the reinf...
Schizophrenia, a serious mental illness, is associated with evidence of NMDA receptor (NMDAR) dysfunction and characterized by cognitive impairments that reflect impaired value updating and feedback-driven control; however the cellular and circuit-level mechanisms underlying these disruptions remain unclear. Here we te...
Purpose This paper aims to address a core limitation in computational Kantian ethics: the tension between deontological rigidity and the demands of decision-making in complex, real-world environments. It proposes an adaptive extension of the categorical imperative that preserves its non-consequentialist foundations whi...
A Blog post by Ai2 on Hugging Face
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
Learn how Google Antigravity and our Cheminformatics Skills accelerate drug discovery workflows, search compounds, and propose novel rigidified macrocycles.
Prabha Jha used her experience with MIT Open Learning’s program for senior executives to develop AI solutions for her employer, Verizon, and to write a book.
Education Innovation
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
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