13 citations · 19 across the 6 of their papers we have counts for
9 papers
On the Importance of Asymmetry for Siamese Representation Learning
Xiao Wang, Haoqi Fan, Yuandong Tian +2
Many recent self-supervised frameworks for visual representation learning are based on certain forms of Siamese networks. Such networks are conceptually symmetric with two parallel…
SHREC 2021: Classification in cryo-electron tomograms
Ilja Gubins, Marten L. Chaillet, Gijs van der Schot +20
Cryo-electron tomography (cryo-ET) is an imaging technique that allows three-dimensional visualization of macro-molecular assemblies under near-native conditions. Cryo-ET comes wit…
Using Steered Molecular Dynamic Tension for Assessing Quality of Computational Protein Structure Models
Lyman Monroe, Daisuke Kihara
The native structures of proteins, except for notable exceptions of intrinsically disordered proteins, in general take their most stable conformation in the physiological condition…
Application of Sequence Embedding in Protein Sequence-Based Predictions
Nabil Ibtehaz, Daisuke Kihara
In sequence-based predictions, conventionally an input sequence is represented by a multiple sequence alignment (MSA) or a representation derived from MSA, such as a position-speci…
SHREC 2021: Retrieval and classification of protein surfaces equipped with physical and chemical properties
Andrea Raffo, Ulderico Fugacci, Silvia Biasotti +21
This paper presents the methods that have participated in the SHREC 2021 contest on retrieval and classification of protein surfaces on the basis of their geometry and physicochemi…
EnAET: A Self-Trained framework for Semi-Supervised and Supervised Learning with Ensemble Transformations
Xiao Wang, Daisuke Kihara, Jiebo Luo +1
Deep neural networks have been successfully applied to many real-world applications. However, such successes rely heavily on large amounts of labeled data that is expensive to obta…