Zobrazeno 1 - 10
of 76 268
pro vyhledávání: '"A. Eaton"'
Autor:
Voelcker, Claas A, Hussing, Marcel, Eaton, Eric, Farahmand, Amir-massoud, Gilitschenski, Igor
Building deep reinforcement learning (RL) agents that find a good policy with few samples has proven notoriously challenging. To achieve sample efficiency, recent work has explored updating neural networks with large numbers of gradient steps for eve
Externí odkaz:
http://arxiv.org/abs/2410.08896
Empirical, benchmark-driven testing is a fundamental paradigm in the current RL community. While using off-the-shelf benchmarks in reinforcement learning (RL) research is a common practice, this choice is rarely discussed. Benchmark choices are often
Externí odkaz:
http://arxiv.org/abs/2410.08870
Autor:
Le, Long, Xie, Jason, Liang, William, Wang, Hung-Ju, Yang, Yue, Ma, Yecheng Jason, Vedder, Kyle, Krishna, Arjun, Jayaraman, Dinesh, Eaton, Eric
Interactive 3D simulated objects are crucial in AR/VR, animations, and robotics, driving immersive experiences and advanced automation. However, creating these articulated objects requires extensive human effort and expertise, limiting their broader
Externí odkaz:
http://arxiv.org/abs/2410.13882
Autor:
Vedder, Kyle, Peri, Neehar, Khatri, Ishan, Li, Siyi, Eaton, Eric, Kocamaz, Mehmet, Wang, Yue, Yu, Zhiding, Ramanan, Deva, Pehserl, Joachim
We reframe scene flow as the task of estimating a continuous space-time ODE that describes motion for an entire observation sequence, represented with a neural prior. Our method, EulerFlow, optimizes this neural prior estimate against several multi-o
Externí odkaz:
http://arxiv.org/abs/2410.02031
Autor:
Eaton, Andrew, Kuthanazhi, Brinda, Canfield, Paul C., Schrunk, Benjamin, Jo, Na Hyun, Kushnirenko, Yevhen, O'Leary, Evan, Wang, Lin-Lin, Kaminski, Adam
Publikováno v:
Phys. Rev. B 110, 125150 (2024)
EuAl$_4$ is proposed to host a topological Hall state. This material also undergoes four consecutive antiferromagnetic (AFM) transitions upon cooling below TN1 = 15.4 K in the presence of charge density wave (CDW) order that sets in below TCDW = 140
Externí odkaz:
http://arxiv.org/abs/2409.16468
Autor:
Qiwei, Li, Zhang, Shihui, Kasper, Andrew Timothy, Ashkinaze, Joshua, Eaton, Asia A., Schoenebeck, Sarita, Gilbert, Eric
Non-consensual intimate media (NCIM) inflicts significant harm. Currently, victim-survivors can use two mechanisms to report NCIM - as a non-consensual nudity violation or as copyright infringement. We conducted an audit study of takedown speed of NC
Externí odkaz:
http://arxiv.org/abs/2409.12138
Autor:
Kushnirenko, Yevhen, Kuthanazhi, Brinda, Schrunk, Benjamin, O'Leary, Evan, Eaton, Andrew, Slager, Robert-Jan, Ahn, Junyeong, Wang, Lin-Lin, Canfield, Paul C., Kaminski, Adam
We perform angle-resolved photoemission spectroscopy (ARPES) measurements in conjunction with density functional theory (DFT) calculations to investigate the evolution of the electronic structure of CeBi upon a series of antiferromagnetic (AFM) trans
Externí odkaz:
http://arxiv.org/abs/2409.08125
Autor:
Mariano, Lorenzo A., Nguyen, Vu Ha Anh, Petersen, Jonatan B., Björnsson, Magnus, Bendix, Jesper, Eaton, Gareth R., Eaton, Sandra S., Lunghi, Alessandro
Magnetic resonance is a prime method for the study of chemical and biological structures and their dynamical processes. The interpretation of many of these experiments relies on understanding how the spin of unpaired electrons exchanges energy with t
Externí odkaz:
http://arxiv.org/abs/2407.01380
Autor:
Dehghani, Farzaneh, Dibaji, Mahsa, Anzum, Fahim, Dey, Lily, Basdemir, Alican, Bayat, Sayeh, Boucher, Jean-Christophe, Drew, Steve, Eaton, Sarah Elaine, Frayne, Richard, Ginde, Gouri, Harris, Ashley, Ioannou, Yani, Lebel, Catherine, Lysack, John, Arzuaga, Leslie Salgado, Stanley, Emma, Souza, Roberto, Santos, Ronnie de Souza, Wells, Lana, Williamson, Tyler, Wilms, Matthias, Wahid, Zaman, Ungrin, Mark, Gavrilova, Marina, Bento, Mariana
Artificial Intelligence (AI) has paved the way for revolutionary decision-making processes, which if harnessed appropriately, can contribute to advancements in various sectors, from healthcare to economics. However, its black box nature presents sign
Externí odkaz:
http://arxiv.org/abs/2408.15550
Assessing Modality Bias in Video Question Answering Benchmarks with Multimodal Large Language Models
Autor:
Park, Jean, Jang, Kuk Jin, Alasaly, Basam, Mopidevi, Sriharsha, Zolensky, Andrew, Eaton, Eric, Lee, Insup, Johnson, Kevin
Multimodal large language models (MLLMs) can simultaneously process visual, textual, and auditory data, capturing insights that complement human analysis. However, existing video question-answering (VidQA) benchmarks and datasets often exhibit a bias
Externí odkaz:
http://arxiv.org/abs/2408.12763