Results 41 to 50 of about 3,629,477 (294)
Multivariate Time Series Information Bottleneck
Entropy, 2023 Time series (TS) and multiple time series (MTS) predictions have historically paved the way for distinct families of deep learning models. The temporal dimension, distinguished by its evolutionary sequential aspect, is usually modeled by decomposition ...
Denis Ullmann +2 more
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Perturbation AUTOVC: Voice Conversion From Perturbation and Autoencoder Loss
IEEE Access, 2023 AUTOVC is a voice-conversion method that performs self-reconstruction using an autoencoder structure for zero-shot voice conversion. AUTOVC has the advantage of being easy and simple to learn because it only uses the autoencoder loss for learning ...
Hwa-Young Park +2 more
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Function Identification in Neuron Populations via Information Bottleneck
Entropy, 2013 It is plausible to hypothesize that the spiking responses of certain neurons represent functions of the spiking signals of other neurons. A natural ensuing question concerns how to use experimental data to infer what kind of a function is being computed.
S. Kartik Buddha +3 more
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Towards socially adaptive robots : A novel method for real time recognition of human-robot interaction styles [PDF]
, 2009 “This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders.
Dautenhahn, K., Francois, D., Polani, D.
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Image-Based Ship Detection Using Deep Variational Information Bottleneck
Sensors, 2023 Image-based ship detection is a critical function in maritime security. However, lacking high-quality training datasets makes it challenging to train a robust supervision deep learning model.
Duc-Dat Ngo +4 more
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Acoustic Model Construction Method Based on Bottleneck Compound Feature [PDF]
Jisuanji gongcheng, 2020 The Mel-Frequency Cepstral Coefficient(MFCC) speech features cannot effectively reflect the effective information between consecutive frames.To address the problem,this paper uses deep neural network to extract bottleneck features with long-term ...
ZHENG Wenxiu, ZHAO Junyi, WEN Xinyi, YAO Yindi
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Quantifying Morphological Computation
Entropy, 2013 The field of embodied intelligence emphasises the importance of the morphology and environment with respect to the behaviour of a cognitive system. The contribution of the morphology to the behaviour, commonly known as morphological computation, is well ...
Nihat Ay, Keyan Zahedi
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Fast and Lightweight Human Pose Estimation
IEEE Access, 2021 Although achieving significant improvement on pose estimation, the major drawback is that most top-performing methods tend to adopt complex architecture and spend large computational cost to achieve higher performance.
Haopan Ren +5 more
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XLIndy: interactive recognition and information extraction in spreadsheets [PDF]
, 2019 Over the years, spreadsheets have established their presence in many domains, including business, government, and science. However, challenges arise due to spreadsheets being partially-structured and carrying implicit (visual and textual) information ...
Gonsior, Julius +7 more
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Embo: a Python package for empirical data analysis using the Information Bottleneck
Journal of Open Research Software, 2021 We present 'embo', a Python package to analyze empirical data using the Information Bottleneck (IB) method and its variants, such as the Deterministic Information Bottleneck (DIB).
Eugenio Piasini +3 more
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