Zobrazeno 1 - 10
of 61 145
pro vyhledávání: '"A. Aki"'
We propose ratio divergence (RD) learning for discrete energy-based models, a method that utilizes both training data and a tractable target energy function. We apply RD learning to restricted Boltzmann machines (RBMs), which are a minimal model that
Externí odkaz:
http://arxiv.org/abs/2409.07679
Autor:
Schmitt, Marvin, Li, Chengkun, Vehtari, Aki, Acerbi, Luigi, Bürkner, Paul-Christian, Radev, Stefan T.
Bayesian inference often faces a trade-off between computational speed and sampling accuracy. We propose an adaptive workflow that integrates rapid amortized inference with gold-standard MCMC techniques to achieve both speed and accuracy when perform
Externí odkaz:
http://arxiv.org/abs/2409.04332
Autor:
Makarov, Sergey S., Grigoryev, Sergey A., Zhakhovsky, Vasily V., Chuprov, Petr, Pikuz, Tatiana A., Inogamov, Nail A., Khokhlov, Victor V., Petrov, Yuri V., Perov, Eugene, Shepelev, Vadim, Shobu, Takehisa, Tominaga, Aki, Rapp, Ludovic, Rode, Andrei V., Juodkazis, Saulius, Makita, Mikako, Nakatsutsumi, Motoaki, Preston, Thomas R., Appel, Karen, Konopkova, Zuzana, Cerantola, Valerio, Brambrink, Erik, Schwinkendorf, Jan-Patrick, Mohacsi, István, Vozda, Vojtech, Hajkova, Vera, Burian, Tomas, Chalupsky, Jaromir, Juha, Libor, Ozaki, Norimasa, Kodama, Ryosuke, Zastrau, Ulf, Pikuz, Sergey A.
Sub-picosecond optical laser processing of metals is actively utilized for modification of a heated surface layer. But for deeper modification of different materials a laser in the hard x-ray range is required. Here, we demonstrate that a single 9-ke
Externí odkaz:
http://arxiv.org/abs/2409.03625
Active learning (AL) has shown promise for being a particularly data-efficient machine learning approach. Yet, its performance depends on the application and it is not clear when AL practitioners can expect computational savings. Here, we carry out a
Externí odkaz:
http://arxiv.org/abs/2408.11191
Autor:
Yokouchi, Tomoyuki, Kitaori, Aki, Yamaguchi, Daiki, Kanazawa, Naoya, Hirschberger, Max, Nagaosa, Naoto, Tokura, Yoshinori
When non-collinear spin textures are driven by current, an emergent electric field arises due to the emergent electromagnetic induction. So far, this phenomenon has been reported in several materials, manifesting the current-nonlinear imaginary part
Externí odkaz:
http://arxiv.org/abs/2407.15682
Large pretrained self-attention neural networks, or transformers, have been very successful in various tasks recently. The performance of a model on a given task depends on its ability to memorize and generalize the training data. Large transformer m
Externí odkaz:
http://arxiv.org/abs/2407.15425
Autor:
Härmä, Aki, Brinker, Bert den, Grossekathofer, Ulf, Ouweltjes, Okke, Nallanthighal, Srikanth, Abrol, Sidharth, Sharma, Vibhu
Recent years has witnessed an increase in technologies that use speech for the sensing of the health of the talker. This survey paper proposes a general taxonomy of the technologies and a broad overview of current progress and challenges. Vocal bioma
Externí odkaz:
http://arxiv.org/abs/2407.17505
Autor:
Magnusson, Måns, Torgander, Jakob, Bürkner, Paul-Christian, Zhang, Lu, Carpenter, Bob, Vehtari, Aki
The generality and robustness of inference algorithms is critical to the success of widely used probabilistic programming languages such as Stan, PyMC, Pyro, and Turing.jl. When designing a new general-purpose inference algorithm, whether it involves
Externí odkaz:
http://arxiv.org/abs/2407.04967
Autor:
Fèvre, Patrick Le, Salazar, Raphaël, Jamet, Matthieu, Bertran, François, Bigi, Chiara, Ourghi, Abdelkarim, Vergnaud, Céline, Pulkkinen, Aki, Minar, Jan, Jaouen, Thomas, Rault, Julien
Transition Metal Dichalcogenides (TMD) are layered materials obtained by stacking two-dimensional sheets weakly bonded by van der Waals interactions. In bulk TMD, band dispersions are observed in the direction normal to the sheet plane (z-direction)
Externí odkaz:
http://arxiv.org/abs/2407.03768
Creating systems capable of generating virtually infinite variations of complex and novel behaviour without predetermined goals or limits is a major challenge in the field of AI. This challenge has been addressed through the development of several op
Externí odkaz:
http://arxiv.org/abs/2406.04663