Results 31 to 40 of about 114,527 (276)
Effective Dynamics of Generative Adversarial Networks
Physical Review X, 2023 Generative adversarial networks (GANs) are a class of machine-learning models that use adversarial training to generate new samples with the same (potentially very complex) statistics as the training samples.
Steven Durr +3 more
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O OBOWIĄZYWANIU ZASADY KONTRADYKTORYJNOŚCI W POSTĘPOWANIU NIEPROCESOWYM: PRZYCZYNEK DO DYSKUSJI
Zeszyty Prawnicze, 2016 The Adversarial Principle in Non-litigious Proceedings: a Contribution to the Discussion Summary The adversarial principle has been applicable in Polish non-litigious proceedings since 1964, when the provisions for litigious and non-litigious ...
Joanna Misztal-Konecka
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Adaptive Density Estimation for Generative Models [PDF]
, 2019 Unsupervised learning of generative models has seen tremendous progress over recent years, in particular due to generative adversarial networks (GANs), variational autoencoders, and flow-based models.
Alahari, Karteek +4 more
core +2 more sources
Active Learning‐Guided Accelerated Discovery of Ultra‐Efficient High‐Entropy Thermoelectrics
Advanced Materials, EarlyView.An active learning framework is introduced for the accelerated discovery of high‐entropy chalcogenides with superior thermoelectric performance. Only 80 targeted syntheses, selected from 16206 possible combinations, led to three high‐performance compositions, demonstrating the remarkable efficiency of data‐driven guidance in experimental materials ...
Hanhwi Jang +8 more
wiley +1 more source
THE ADVERSARIAL PRINCIPLE AND THE BALANCE OF PUBLIC AND PRIVATE IN CRIMINAL PROCEEDINGS
Правовое государство: теория и практикаThe proper understanding of the principles of adversarial proceedings and equality of the parties before the court in the administration of criminal proceedings was seriously transformed during the period of operation of the Criminal Procedure Code of ...
SOLOVIEV Sergey Alexandrovich
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Semi-Supervised Adversarial Variational Autoencoder
Machine Learning and Knowledge Extraction, 2020 We present a method to improve the reconstruction and generation performance of a variational autoencoder (VAE) by injecting an adversarial learning. Instead of comparing the reconstructed with the original data to calculate the reconstruction loss, we ...
Ryad Zemouri
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Certifying Some Distributional Robustness with Principled Adversarial Training
, 2017 ICLR 2018: https://openreview.net/forum?id=Hk6kPgZA-
Sinha, Aman +3 more
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Organic Electrochemical Transistors for Neuromorphic Devices and Applications
Advanced Materials, EarlyView.Organic electrochemical transistors are emerging as promising platforms for neuromorphic devices that emulate neuronal and synaptic activities and can seamlessly integrate with biological systems. This review focuses on resultant organic artificial neurons, synapses, and integrated devices, with an emphasis on their ability to perform neuromorphic ...
Kexin Xiang +4 more
wiley +1 more source
Adversarial Principle within International Commercial Arbitration
Uzhhorod National University Herald. Series: LawThe effect of the adversarial principle within international commercial arbitration has been studied in the article. It has been noted that the ever-growing development of economic relations inextricably leads to an increase in disputes in the field of economic activity.
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InfoAT: Improving Adversarial Training Using the Information Bottleneck Principle
IEEE Transactions on Neural Networks and Learning SystemsAdversarial training (AT) has shown excellent high performance in defending against adversarial examples. Recent studies demonstrate that examples are not equally important to the final robustness of models during AT, that is, the so-called hard examples that can be attacked easily exhibit more influence than robust examples on the final robustness ...
Mengting Xu +3 more
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