TH2.AUD.5
DISCRETE REPRESENTATION LEARNING FOR MULTIVARIATE TIME SERIES
Marzieh Ajirak, Immanuel Elbau, Nili Solomonov, Logan Grosenick, Weill Cornell Medicine, United States
Session:
TH2.AUD: Exploring Synergies: Advancing Neuroscience with Machine Learning Lecture
Track:
Special Sessions
Location:
Auditorium
Presentation Time:
Thu, 29 Aug, 15:20 - 15:40 France Time (UTC +1)
Session Co-Chairs:
Petar Djuric, Stony Brook University and Marzieh Ajirak, Weill Cornell Medicine
Presentation
Discussion
Resources
No resources available.
Session TH2.AUD
TH2.AUD.1: FUSION OF NOVEL FMRI FEATURES USING INDEPENDENT VECTOR ANALYSIS FOR A MULTIFACETED CHARACTERIZATION OF SCHIZOPHRENIA
Chunying Jia, Mohammad Abu Baker Siddique Akhonda, Hanlu Yang, University of Maryland Baltimore County, United States; Vince D. Calhoun, Georgia State University, Georgia Institute of Technology, Emory University, United States; Tülay Adali, University of Maryland Baltimore County, United States
TH2.AUD.2: Distributed Beamforming for Localization of Brain Seizure Sources from Intracranial EEG Array
Sepehr Shirani, Nottingham Trent University, United Kingdom; Bahman Abdi-Sargezeh, University of Oxford, United Kingdom; Antonio Valentin, King’s College London, United Kingdom; Gonzalo Alarcon, University of Manchester, United Kingdom; Delaram Jarchi, University of Essex, United Kingdom; Jordan Bird, Nottingham Trent University, United Kingdom; Saeid Sanei, Imperial College London, United Kingdom
TH2.AUD.3: Gaussian Process-based Inference toward Revealing Brain Functional Connectivity
Chen Cui, Stony Brook University, United States; Sima Mofakham, Renaissance School of Medicine at Stony Brook University, United States; Jessica Phillips, University of Wisconsin-Madison, United States; Kurt Butler, Stony Brook University, United States; Charles Mikell, Renaissance School of Medicine at Stony Brook University, United States; Yuri Saalmann, University of Wisconsin-Madison, United States; Petar Djuric, Stony Brook University, United States
TH2.AUD.4: REAL-TIME MACHINE LEARNING STRATEGIES FOR A NEW KIND OF NEUROSCIENCE EXPERIMENTS
Ayesha Vermani, Matthew Dowling, Hyungju Jeon, Champalimaud Centre for the Unknown, Portugal; Ian Jordan, Josue Nassar, RyvivyR, United States; Yves Bernaerts, Champalimaud Centre for the Unknown, Portugal; Yuan Zhao, National Institute of Mental Health, United States; Steven Van Vaerenbergh, University of Cantabria, Spain; Il Memming Park, Champalimaud Centre for the Unknown, Portugal
TH2.AUD.5: DISCRETE REPRESENTATION LEARNING FOR MULTIVARIATE TIME SERIES
Marzieh Ajirak, Immanuel Elbau, Nili Solomonov, Logan Grosenick, Weill Cornell Medicine, United States