Results 41 to 50 of about 33,606 (255)

EAT-C: Environment-Adversarial sub-Task Curriculum for RL

, 2023
Reinforcement learning (RL) is inefficient on long-horizon tasks due to sparse rewards and its policy can be fragile to slightly perturbed environments.
Jiang, J, Song, X, Ao, S, Zhou, T, Long, G, Zhang, C   +5 more
core  

Inverse Design of Amorphous Materials With Targeted Properties

Advanced Materials, EarlyView.
AMDEN is a diffusion model framework for the inverse design of amorphous materials with targeted properties. By incorporating Hamiltonian Monte Carlo refinement into the denoising process, the framework overcomes the challenge of generating thermally relaxed disordered structures.
Jonas A. Finkler, Yan Lin, Tao Du, Jilin Hu, Morten M. Smedskjaer   +4 more
wiley   +1 more source

Evaluating Realistic Adversarial Attacks against Machine Learning Models for Windows PE Malware Detection

Future Internet
During the last decade, the cybersecurity literature has conferred a high-level role to machine learning as a powerful security paradigm to recognise malicious software in modern anti-malware systems.
Muhammad Imran, Annalisa Appice, Donato Malerba   +2 more
doaj   +1 more source

Advancing Lithium–Oxygen Batteries: Pioneering Cathode Catalyst Innovation and Artificial Intelligence‐Driven Design Paradigms

Advanced Materials, EarlyView.
This review summarizes the principles and challenges of nonaqueous lithium‐oxygen batteries and recent advances in cathode catalysts, including carbon‐based materials, metals, oxides, sulfides, nitrides, carbides, and redox mediators. It highlights emerging design strategies and artificial intelligence‐driven approaches, emphasizing data‐assisted ...
Yuqing Yao, Chongyang Hao, Karol Viviana Mejia‐Centeno, Malik Dilshad Khan, Shang Wang, Longqiu Li, Yanhong Tian, Andreu Cabot, Qing Sun   +8 more
wiley   +1 more source

A Systematic Review of Adversarial Machine Learning and Deep Learning Applications

Al-Iraqia Journal for Scientific Engineering Research
The review delves into creating an understandable framework for machine learning in robotics. It stresses the significance of machine learning in materials science and robotics highlighting how it can transform industries by boosting efficiency and ...
Tabarak Ali Abdalkareem, Khamis A. Zidan, A. S. Albahri   +2 more
doaj   +1 more source

Investigation of the impact effectiveness of adversarial data leakage attacks on the machine learning models [PDF]

ITM Web of Conferences
Machine learning solutions have been successfully applied in many aspects, so it is now important to ensure the security of the machine learning models themselves and develop appropriate solutions and approaches.
Parfenov Denis, Grishina Lubov, Zhigalov Artur, Parfenov Anton   +3 more
doaj   +1 more source

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

Advanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz, Yaroslav Mudryk, Jun Cui, Lucas Griffith, Duane D. Johnson, Julie Slaughter   +5 more
wiley   +1 more source

Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space

Advanced Robotics Research, EarlyView.
A quadruped robot masters dynamic jumps through constrained spaces with animal‐inspired moves and intelligent vision control. This hierarchical learning approach combines imitation of biological agility with real‐time trajectory planning. Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating ...
Zeren Luo, Jiahui Zhang, Yimin Han, Ji Ma, Minghao Lu, Ioannis Havoutis, Peng Lu   +6 more
wiley   +1 more source

SURVEY AND PROPOSED METHOD TO DETECT ADVERSARIAL EXAMPLES USING AN ADVERSARIAL RETRAINING MODEL

Tạp chí Khoa học Đại học Đà Lạt
Artificial intelligence (AI) has found applications across various sectors and industries, offering numerous advantages to human beings. One prominent area where AI has made significant contributions is in machine learning models.
Thanh Son Phan, Quang Hua Ta, Duy Trung Pham, Phi Ho Truong   +3 more
doaj   +1 more source

Gaussian mixture variational autoencoder for collaborative filtering

四川大学学报. 自然科学版, 2023
Currently, machine learning-based detectors are widely used to handle millions of Android malware, but they often suffer from poor anti-adversarial attack abilities.
ZHANG Yu-Ke, WANG Jun-Feng
doaj