Zobrazeno 1 - 10
of 38 560
pro vyhledávání: '"P A, Williamson"'
We introduce PatternBoost, a flexible method for finding interesting constructions in mathematics. Our algorithm alternates between two phases. In the first ``local'' phase, a classical search algorithm is used to produce many desirable constructions
Externí odkaz:
http://arxiv.org/abs/2411.00566
We identify and interpret the possible quantum thermal machine regimes with a transverse-field Ising model as the working substance. In general, understanding the emergence of such regimes in a many-body quantum system is challenging due to the depen
Externí odkaz:
http://arxiv.org/abs/2410.23710
What does it mean to say that, for example, the probability for rain tomorrow is between 20% and 30%? The theory for the evaluation of precise probabilistic forecasts is well-developed and is grounded in the key concepts of proper scoring rules and c
Externí odkaz:
http://arxiv.org/abs/2410.23001
Carrying conversations in multi-sound environments is one of the more challenging tasks, since the sounds overlap across time and frequency making it difficult to understand a single sound source. One proposed approach to help isolate an attended spe
Externí odkaz:
http://arxiv.org/abs/2410.18395
Autor:
Dodson, Richard, Williamson, Alex, Gong, Qian, Elahi, Pascal, Wicenec, Andreas, Rioja, Maria J., Chen, Jieyang, Podhorszki, Norbert, Klasky, Scott
The next-generation radio astronomy instruments are providing a massive increase in sensitivity and coverage, through increased stations in the array and frequency span. Two primary problems encountered when processing the resultant avalanche of data
Externí odkaz:
http://arxiv.org/abs/2410.15683
Autor:
Mittmann, Gesa, Laiouar-Pedari, Sara, Mehrtens, Hendrik A., Haggenmüller, Sarah, Bucher, Tabea-Clara, Chanda, Tirtha, Gaisa, Nadine T., Wagner, Mathias, Klamminger, Gilbert Georg, Rau, Tilman T., Neppl, Christina, Compérat, Eva Maria, Gocht, Andreas, Hämmerle, Monika, Rupp, Niels J., Westhoff, Jula, Krücken, Irene, Seidl, Maximillian, Schürch, Christian M., Bauer, Marcus, Solass, Wiebke, Tam, Yu Chun, Weber, Florian, Grobholz, Rainer, Augustyniak, Jaroslaw, Kalinski, Thomas, Hörner, Christian, Mertz, Kirsten D., Döring, Constanze, Erbersdobler, Andreas, Deubler, Gabriele, Bremmer, Felix, Sommer, Ulrich, Brodhun, Michael, Griffin, Jon, Lenon, Maria Sarah L., Trpkov, Kiril, Cheng, Liang, Chen, Fei, Levi, Angelique, Cai, Guoping, Nguyen, Tri Q., Amin, Ali, Cimadamore, Alessia, Shabaik, Ahmed, Manucha, Varsha, Ahmad, Nazeel, Messias, Nidia, Sanguedolce, Francesca, Taheri, Diana, Baraban, Ezra, Jia, Liwei, Shah, Rajal B., Siadat, Farshid, Swarbrick, Nicole, Park, Kyung, Hassan, Oudai, Sakhaie, Siamak, Downes, Michelle R., Miyamoto, Hiroshi, Williamson, Sean R., Holland-Letz, Tim, Schneider, Carolin V., Kather, Jakob Nikolas, Tolkach, Yuri, Brinker, Titus J.
The aggressiveness of prostate cancer, the most common cancer in men worldwide, is primarily assessed based on histopathological data using the Gleason scoring system. While artificial intelligence (AI) has shown promise in accurately predicting Glea
Externí odkaz:
http://arxiv.org/abs/2410.15012
Autor:
Polyak, Adam, Zohar, Amit, Brown, Andrew, Tjandra, Andros, Sinha, Animesh, Lee, Ann, Vyas, Apoorv, Shi, Bowen, Ma, Chih-Yao, Chuang, Ching-Yao, Yan, David, Choudhary, Dhruv, Wang, Dingkang, Sethi, Geet, Pang, Guan, Ma, Haoyu, Misra, Ishan, Hou, Ji, Wang, Jialiang, Jagadeesh, Kiran, Li, Kunpeng, Zhang, Luxin, Singh, Mannat, Williamson, Mary, Le, Matt, Yu, Matthew, Singh, Mitesh Kumar, Zhang, Peizhao, Vajda, Peter, Duval, Quentin, Girdhar, Rohit, Sumbaly, Roshan, Rambhatla, Sai Saketh, Tsai, Sam, Azadi, Samaneh, Datta, Samyak, Chen, Sanyuan, Bell, Sean, Ramaswamy, Sharadh, Sheynin, Shelly, Bhattacharya, Siddharth, Motwani, Simran, Xu, Tao, Li, Tianhe, Hou, Tingbo, Hsu, Wei-Ning, Yin, Xi, Dai, Xiaoliang, Taigman, Yaniv, Luo, Yaqiao, Liu, Yen-Cheng, Wu, Yi-Chiao, Zhao, Yue, Kirstain, Yuval, He, Zecheng, He, Zijian, Pumarola, Albert, Thabet, Ali, Sanakoyeu, Artsiom, Mallya, Arun, Guo, Baishan, Araya, Boris, Kerr, Breena, Wood, Carleigh, Liu, Ce, Peng, Cen, Vengertsev, Dimitry, Schonfeld, Edgar, Blanchard, Elliot, Juefei-Xu, Felix, Nord, Fraylie, Liang, Jeff, Hoffman, John, Kohler, Jonas, Fire, Kaolin, Sivakumar, Karthik, Chen, Lawrence, Yu, Licheng, Gao, Luya, Georgopoulos, Markos, Moritz, Rashel, Sampson, Sara K., Li, Shikai, Parmeggiani, Simone, Fine, Steve, Fowler, Tara, Petrovic, Vladan, Du, Yuming
We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabilities such as precise instruction-based video editing and generation of
Externí odkaz:
http://arxiv.org/abs/2410.13720
Autor:
Corrales, Miguel, Berti, Sean, Denel, Bertrand, Williamson, Paul, Aleardi, Mattia, Ravasi, Matteo
In recent years, Full-Waveform Inversion (FWI) has been extensively used to derive high-resolution subsurface velocity models from seismic data. However, due to the nonlinearity and ill-posed nature of the problem, FWI requires a good starting model
Externí odkaz:
http://arxiv.org/abs/2410.13249
Objective speech quality measures are typically used to assess speech enhancement algorithms, but it has been shown that they are sub-optimal as learning objectives because they do not always align well with human subjective ratings. This misalignmen
Externí odkaz:
http://arxiv.org/abs/2410.13182
Autor:
Kibria, Imran E, Williamson, Donald S.
Speech quality is best evaluated by human feedback using mean opinion scores (MOS). However, variance in ratings between listeners can introduce noise in the true quality label of an utterance. Currently, deep learning networks including convolutiona
Externí odkaz:
http://arxiv.org/abs/2410.12675