Zobrazeno 1 - 10
of 75
pro vyhledávání: '"Jha, Rohan"'
Autor:
Jain, Arnav, Sanjotra, Jasmer Singh, Choudhary, Harshvardhan, Agrawal, Krish, Shah, Rupal, Jha, Rohan, Sajid, M., Hussain, Amir, Tanveer, M.
Publikováno v:
INTERSPEECH 2024
In this paper, we propose long short term memory speech enhancement network (LSTMSE-Net), an audio-visual speech enhancement (AVSE) method. This innovative method leverages the complementary nature of visual and audio information to boost the quality
Externí odkaz:
http://arxiv.org/abs/2409.02266
Autor:
Jha, Rohan, Wang, Bo, Günther, Michael, Mastrapas, Georgios, Sturua, Saba, Mohr, Isabelle, Koukounas, Andreas, Akram, Mohammad Kalim, Wang, Nan, Xiao, Han
Multi-vector dense models, such as ColBERT, have proven highly effective in information retrieval. ColBERT's late interaction scoring approximates the joint query-document attention seen in cross-encoders while maintaining inference efficiency closer
Externí odkaz:
http://arxiv.org/abs/2408.16672
Autor:
Jha, Rohan, Chua, Melissa M.J., Liu, David D., Cosgrove, Garth R., Tobochnik, Steven, Rolston, John D.
Publikováno v:
In Epilepsy & Behavior September 2024 158
Autor:
Jha, Rohan, MJ Chua, Melissa, Nawabi, Noah, Cash, Sydney S., Rolston, John D., Cole, Andrew J.
Publikováno v:
In Epilepsy Research September 2024 205
Autor:
Jha, Rohan1 (AUTHOR) rjha@hms.harvard.edu, Chua, Melissa M. J.2 (AUTHOR), Sarkis, Rani3 (AUTHOR), Tobochnik, Steven3 (AUTHOR), Rolston, John D.1,2 (AUTHOR) jrolston@bwh.harvard.edu
Publikováno v:
Annals of Clinical & Translational Neurology. Jul2024, Vol. 11 Issue 7, p1787-1797. 11p.
Autor:
Jha, Rohan, Chua, Melissa M.J., Liu, David D., Richardson, R. Mark, Tobochnik, Steven, Rolston, John D.
Publikováno v:
In Epilepsy Research December 2024 208
Publikováno v:
In Journal of Clinical Neuroscience February 2024 120:107-114
Autor:
Singh, Hargunbir, Sawal, Nishit, Gupta, Vipin K., Jha, Rohan, Stamm, Michaela, Arjun, Shivani, Gupta, Varsha, Rolston, John D.
Publikováno v:
In Journal of Clinical Neuroscience February 2024 120:76-81
Autor:
Kappel, Ari D.1,2 (AUTHOR) akappel@bwh.harvard.edu, Jha, Rohan1 (AUTHOR) g.saibaba13@gmail.com, Guggilapu, Saibaba1 (AUTHOR) rdu@bwh.harvard.edu, Smith, William J.1,3 (AUTHOR) pokmeng.see@childrens.harvard.edu, Feroze, Abdullah H.1,2 (AUTHOR), Dmytriw, Adam A.1,3 (AUTHOR), Vicenty-Padilla, Juan4 (AUTHOR) rodolfo.alcedo@upr.edu, Alcedo Guardia, Rodolfo E.4 (AUTHOR), Gessler, Florian A.5 (AUTHOR), Patel, Nirav J.1,2 (AUTHOR), Du, Rose1,2 (AUTHOR), See, Alfred P.1,6 (AUTHOR), Peruzzi, Pier Paolo1,2 (AUTHOR), Aziz-Sultan, Mohammad A.1,2 (AUTHOR) asultan@bwh.harvard.edu, Bernstock, Joshua D.1,2 (AUTHOR) asultan@bwh.harvard.edu
Publikováno v:
Cancers. Apr2024, Vol. 16 Issue 8, p1594. 17p.
Neural models often exploit superficial features to achieve good performance, rather than deriving more general features. Overcoming this tendency is a central challenge in areas such as representation learning and ML fairness. Recent work has propos
Externí odkaz:
http://arxiv.org/abs/2004.15012