Neural Network Prediction of Strong Lensing Systems with Domain Adaptation and Uncertainty Quantification

Autor: Agarwal, Shrihan, Ćiprijanović, Aleksandra, Nord, Brian D.

Modeling strong gravitational lenses is computationally expensive for the complex data from modern and next-generation cosmic surveys. Deep learning has emerged as a promising approach for finding lenses and predicting lensing parameters, such as the

Externí odkaz: http://arxiv.org/abs/2411.03334

Movie Gen: A Cast of Media Foundation Models

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

Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference

Autor: Jarugula, Sreevani, Nord, Brian, Gandrakota, Abhijith, Ćiprijanović, Aleksandra

In this work, we present a scalable approach for inferring the dark energy equation-of-state parameter ($w$) from a population of strong gravitational lens images using Simulation-Based Inference (SBI). Strong gravitational lensing offers crucial ins

Externí odkaz: http://arxiv.org/abs/2407.17292

Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets

Autor: Roncoli, Andrea, Ćiprijanović, Aleksandra, Voetberg, Maggie, Villaescusa-Navarro, Francisco, Nord, Brian

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and

Externí odkaz: http://arxiv.org/abs/2311.01588

Attitude toward physical activity in Norwegian patients after total knee or hip replacement: A national survey

Autor: Odd Magne Hals, Anne Marie Fenstad, Ove Nord Furnes, Håvard Østerås, Monica Unsgaard-Tøndel, Ann-Katrin Stensdotter

Publikováno v: Fysioterapeuten, Vol 91, Iss 5, Pp 72-80 (2024)

Background: In Europe, arthroplasty surgeries are increasing while the level of physical activity is decreasing and overweight is rising. A transeuropean project promoting physical activity after total knee- or hip replacement was conducted. As a par

Externí odkaz: https://doaj.org/article/a77919c7ef90475d8b78b8d64e7b92fb