Results 91 to 100 of about 8,328,816 (311)
Advanced Science, EarlyView.This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Attack and Defense in Cellular Decision-Making: Lessons from Machine Learning
Physical Review X, 2019 Machine-learning algorithms can be fooled by small well-designed adversarial perturbations. This is reminiscent of cellular decision-making where ligands (called antagonists) prevent correct signaling, like in early immune recognition.
Thomas J. Rademaker +2 more
doaj +1 more source
A survey of practical adversarial example attacks
Cybersecurity, 2018 Adversarial examples revealed the weakness of machine learning techniques in terms of robustness, which moreover inspired adversaries to make use of the weakness to attack systems employing machine learning.
Lu Sun, Mingtian Tan, Zhe Zhou
doaj +1 more source
Adversarial attacks on medical machine learning
Science, 2019 Emerging vulnerabilities demand new ...
Finlayson, Samuel G. +5 more
openaire +4 more sources
Advanced Science, EarlyView.Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li +6 more
wiley +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Advanced Science, EarlyView.Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
StackingNet: Collective Inference Across Independent AI Foundation Models
Advanced Science, EarlyView.ABSTRACT Artificial intelligence (AI) built on large foundation models has transformed language understanding, computer vision, and reasoning, yet these systems remain isolated and cannot readily share their capabilities. Coordinating the complementary strengths of independently developed, black‐box foundation models is essential for trustworthy ...
Siyang Li +4 more
wiley +1 more source
Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, 2019 Perceptual ad-blocking is a novel approach that detects online advertisements based on their visual content. Compared to traditional filter lists, the use of perceptual signals is believed to be less prone to an arms race with web publishers and ad networks. We demonstrate that this may not be the case.
Florian Tramèr +4 more
openaire +2 more sources
195208Adversarial attacks pose a significant threat to the reliability and trustworthiness of machine learning systems, particularly in image classification tasks like deepfake detection.
Bunzel, Niklas +4 more
core +1 more source
The need for open source software in machine learning [PDF]
, 2007 Open source tools have recently reached a level of maturity which makes them suitable for building large-scale real-world systems. At the same time, the field of machine learning has developed a large body of powerful learning algorithms for diverse ...
Ratsch, Gunnar +55 more
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