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of 849
pro vyhledávání: '"Gilra A"'
Learning representations of underlying environmental dynamics from partial observations is a critical challenge in machine learning. In the context of Partially Observable Markov Decision Processes (POMDPs), state representations are often inferred f
Externí odkaz:
http://arxiv.org/abs/2411.07832
The rising successes of RL are propelled by combining smart algorithmic strategies and deep architectures to optimize the distribution of returns and visitations over the state-action space. A quantitative framework to compare the learning processes
Externí odkaz:
http://arxiv.org/abs/2402.09113
Autor:
Yik, Jason, Berghe, Korneel Van den, Blanken, Douwe den, Bouhadjar, Younes, Fabre, Maxime, Hueber, Paul, Ke, Weijie, Khoei, Mina A, Kleyko, Denis, Pacik-Nelson, Noah, Pierro, Alessandro, Stratmann, Philipp, Sun, Pao-Sheng Vincent, Tang, Guangzhi, Wang, Shenqi, Zhou, Biyan, Ahmed, Soikat Hasan, Joseph, George Vathakkattil, Leto, Benedetto, Micheli, Aurora, Mishra, Anurag Kumar, Lenz, Gregor, Sun, Tao, Ahmed, Zergham, Akl, Mahmoud, Anderson, Brian, Andreou, Andreas G., Bartolozzi, Chiara, Basu, Arindam, Bogdan, Petrut, Bohte, Sander, Buckley, Sonia, Cauwenberghs, Gert, Chicca, Elisabetta, Corradi, Federico, de Croon, Guido, Danielescu, Andreea, Daram, Anurag, Davies, Mike, Demirag, Yigit, Eshraghian, Jason, Fischer, Tobias, Forest, Jeremy, Fra, Vittorio, Furber, Steve, Furlong, P. Michael, Gilpin, William, Gilra, Aditya, Gonzalez, Hector A., Indiveri, Giacomo, Joshi, Siddharth, Karia, Vedant, Khacef, Lyes, Knight, James C., Kriener, Laura, Kubendran, Rajkumar, Kudithipudi, Dhireesha, Liu, Yao-Hong, Liu, Shih-Chii, Ma, Haoyuan, Manohar, Rajit, Margarit-Taulé, Josep Maria, Mayr, Christian, Michmizos, Konstantinos, Muir, Dylan, Neftci, Emre, Nowotny, Thomas, Ottati, Fabrizio, Ozcelikkale, Ayca, Panda, Priyadarshini, Park, Jongkil, Payvand, Melika, Pehle, Christian, Petrovici, Mihai A., Posch, Christoph, Renner, Alpha, Sandamirskaya, Yulia, Schaefer, Clemens JS, van Schaik, André, Schemmel, Johannes, Schmidgall, Samuel, Schuman, Catherine, Seo, Jae-sun, Sheik, Sadique, Shrestha, Sumit Bam, Sifalakis, Manolis, Sironi, Amos, Stewart, Matthew, Stewart, Kenneth, Stewart, Terrence C., Timcheck, Jonathan, Tömen, Nergis, Urgese, Gianvito, Verhelst, Marian, Vineyard, Craig M., Vogginger, Bernhard, Yousefzadeh, Amirreza, Zohora, Fatima Tuz, Frenkel, Charlotte, Reddi, Vijay Janapa
Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it difficult to accu
Externí odkaz:
http://arxiv.org/abs/2304.04640
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-20 (2024)
Abstract Task-switching is a fundamental cognitive ability that allows animals to update their knowledge of current rules or contexts. Detecting discrepancies between predicted and observed events is essential for this process. However, little is kno
Externí odkaz:
https://doaj.org/article/c26d291d06fb4946b0c1ed801bb72dce
Publikováno v:
Journal of Oral Biology and Craniofacial Research, Vol 14, Iss 1, Pp 33-38 (2024)
The permanence of deep subgingival restorations are questionable both functionally and biologically. Crown lengthening is one of the traditionally performing procedures to visualize and relocate the deep margins, but the limitations of the invasive s
Externí odkaz:
https://doaj.org/article/7055d81fa678419a8064e0ad5a8bc887
Publikováno v:
In Journal of Oral Biology and Craniofacial Research January-February 2024 14(1):33-38
Autor:
Klos, Christian, Kossio, Yaroslav Felipe Kalle, Goedeke, Sven, Gilra, Aditya, Memmesheimer, Raoul-Martin
Publikováno v:
Phys. Rev. Lett. 125, 088103 (2020)
The ability of humans and animals to quickly adapt to novel tasks is difficult to reconcile with the standard paradigm of learning by slow synaptic weight modification. Here we show that fixed-weight neural networks can learn to generate required dyn
Externí odkaz:
http://arxiv.org/abs/1902.02875
Akademický článek
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Autor:
Chao Han, Gwendolyn English, Hannes P Saal, Giacomo Indiveri, Aditya Gilra, Wolfger von der Behrens, Eleni Vasilaki
Publikováno v:
PLoS Computational Biology, Vol 19, Iss 5, p e1009616 (2023)
In complex natural environments, sensory systems are constantly exposed to a large stream of inputs. Novel or rare stimuli, which are often associated with behaviorally important events, are typically processed differently than the steady sensory bac
Externí odkaz:
https://doaj.org/article/eab48f64f03e4cf9b60ed5628afb172e
Autor:
Gilra, Aditya, Gerstner, Wulfram
Publikováno v:
Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1773-1782, 2018
Learning weights in a spiking neural network with hidden neurons, using local, stable and online rules, to control non-linear body dynamics is an open problem. Here, we employ a supervised scheme, Feedback-based Online Local Learning Of Weights (FOLL
Externí odkaz:
http://arxiv.org/abs/1712.10158