Results 31 to 40 of about 351,687 (262)

Simplicial Complex Representation Learning

, 2021
Simplicial complexes form an important class of topological spaces that are frequently used in many application areas such as computer-aided design, computer graphics, and simulation. Representation learning on graphs, which are just 1-d simplicial complexes, has witnessed a great attention in recent years.
Hajij, Mustafa, Zamzmi, Ghada, Papamarkou, Theodore, Maroulas, Vasileios, Cai, Xuanting   +4 more
openaire   +3 more sources

An Optimized Network Representation Learning Algorithm Using Multi-Relational Data

Mathematics, 2019
Representation learning aims to encode the relationships of research objects into low-dimensional, compressible, and distributed representation vectors.
Zhonglin Ye, Haixing Zhao, Ke Zhang, Yu Zhu, Zhaoyang Wang   +4 more
doaj   +1 more source

Learning Disentangled Discrete Representations

, 2023
Recent successes in image generation, model-based reinforcement learning, and text-to-image generation have demonstrated the empirical advantages of discrete latent representations, although the reasons behind their benefits remain unclear. We explore the relationship between discrete latent spaces and disentangled representations by replacing the ...
Friede, David, Reimers, Christian, Stuckenschmidt, Heiner, Niepert, Mathias   +3 more
openaire   +3 more sources

Efficient Smooth Tensor Train and Tensor Ring Completion for Image Classification Enhancement

IEEE Access
This paper deals with studying the data completion problem for enhancing the image classification task under the pixel removal scenario. In some applications, it happens that a part of the pixels of a given image is lost due to several issues, such as ...
Salman Ahmadi-Asl, Roman V. Garaev, Rustam A. Lukmanov, Naeim Rezaeian, Asad Masood Khattak, Manuel Mazzara   +5 more
doaj   +1 more source

Disentangled Representation Learning

IEEE Transactions on Pattern Analysis and Machine Intelligence
Accepted by IEEE Transactions on Pattern Analysis and Machine ...
Xin Wang, Hong Chen, Si'ao Tang, Zihao Wu, Wenwu Zhu   +4 more
openaire   +3 more sources

Assessing the adversarial robustness of multimodal medical AI systems: insights into vulnerabilities and modality interactions

Frontiers in Medicine
The emergence of both task-specific single-modality models and general-purpose multimodal large models presents new opportunities, but also introduces challenges, particularly regarding adversarial attacks.
Ekaterina Mozhegova, Asad Masood Khattak, Adil Khan, Roman Garaev, Bader Rasheed, Muhammad Shahid Anwar   +5 more
doaj   +1 more source

Stressful Events Reported by Childhood Cancer Survivors and Community Controls From the St. Jude Lifetime (SJLIFE) Cohort: A Mixed Method Study

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Introduction Characterizing stressful events reported by childhood cancer survivors experienced throughout the lifespan may help improve trauma‐informed care relevant to the survivor experience. Methods Participants included 2552 survivors (54% female; 34 years of age) and 469 community controls (62% female; 33 years of age) from the St.
Megan E. Ware, Colter K. Clayton, Fang Wang, Sedigheh Mirzaei, Kyla Shelton, Tara M. Brinkman, Victoria Willard, Katianne M. Howard Sharp, Kevin Krull, Lindsay F. Schwartz, Melissa M. Hudson, Gregory T. Armstrong, Kirsten K. Ness, Rachel T. Webster   +13 more
wiley   +1 more source

Imaging of High‐Risk Neuroblastoma: Recommendations From SIOPEN Radiology and Nuclear Medicine Specialty Committees

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Neuroblastoma is the most common extracranial solid tumor in early childhood. Its clinical behavior is highly variable, ranging from spontaneous regression to fatal outcome despite intensive treatment. The International Society of Pediatric Oncology Europe Neuroblastoma Group (SIOPEN) Radiology and Nuclear Medicine Specialty Committees ...
Annemieke Littooij, Catia Olianti, Herve Brisse, Pier Luigi Di Paolo, Maria Garganese, Tejas Kapadia, Jurgen Schaefer, Hugh Wallace, Simon Wan, Bart de Keizer, Irmina Sefic Pasic, Julian Rogasch   +11 more
wiley   +1 more source

Exploring Preferences for a Digital Single‐Session Intervention for Adolescent Siblings of Youth With Cancer

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Introduction Adolescent siblings of children with cancer are at elevated risk for psychosocial problems. Unfortunately, various barriers such as limited family time and resources, conflicting schedules, and psychosocial staffing constraints at cancer centers hinder sibling access to support.
Christina M. Amaro, Sarah Silver, Prishi Patel, Meredith K. Reffner Collins, Kimberly S. Canter, Stephanie Fooks‐Parker, Michael Amylon, Shawna V. Hudson, Jessica L. Schleider, Melissa A. Alderfer, Katie A. Devine   +10 more
wiley   +1 more source

Learning task-state representations [PDF]

Nature Neuroscience, 2019
Arguably, the most difficult part of learning is deciding what to learn about. Should I associate the positive outcome of safely completing a street-crossing with the situation 'the car approaching the crosswalk was red' or with 'the approaching car was slowing down'?
openaire   +2 more sources