Results 61 to 70 of about 1,274,940 (254)
Learning Robot Activities from First-Person Human Videos Using Convolutional Future Regression
, 2017 We design a new approach that allows robot learning of new activities from unlabeled human example videos. Given videos of humans executing the same activity from a human's viewpoint (i.e., first-person videos), our objective is to make the robot learn ...
Lee, Jangwon, Ryoo, Michael S.
core +1 more source
Deep Representation Learning for Social Network Analysis [PDF]
Frontiers in Big Data, 2019 Social network analysis is an important problem in data mining. A fundamental step for analyzing social networks is to encode network data into low-dimensional representations, i.e., network embeddings, so that the network topology structure and other attribute information can be effectively preserved. Network representation leaning facilitates further
Tan, Qiaoyu, Liu, Ninghao, Hu, Xia
openaire +3 more sources
Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system
FEBS Letters, EarlyView.Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley +1 more source
Learning to count with deep object features
, 2015 Learning to count is a learning strategy that has been recently proposed in the literature for dealing with problems where estimating the number of object instances in a scene is the final objective.
Pujol, Oriol +2 more
core +1 more source
AAA+ protein unfoldases—the Moirai of the proteome
FEBS Letters, EarlyView.AAA+ unfoldases are essential molecular motors that power protein degradation and disaggregation. This review integrates recent cryo‐electron microscopy (cryo‐EM) structures and single‐molecule biophysical data to reconcile competing models of substrate translocation.
Stavros Azinas, Marta Carroni
wiley +1 more source
A Hybrid Approach to Service Recommendation Based on Network Representation Learning
IEEE Access, 2019 Network representation learning has attracted much attention as a new learning paradigm to embed network vertices into a low-dimensional vector space, by preserving network information.
Hao Wu +4 more
doaj +1 more source
GPSP: Graph Partition and Space Projection based Approach for Heterogeneous Network Embedding
, 2018 In this paper, we propose GPSP, a novel Graph Partition and Space Projection based approach, to learn the representation of a heterogeneous network that consists of multiple types of nodes and links.
Du, Wenyu +4 more
core +1 more source
TriNE: Network Representation Learning for Tripartite Heterogeneous Networks [PDF]
2020 IEEE International Conference on Knowledge Graph (ICKG), 2020 In this paper, we study network representation learning for tripartite heterogeneous networks which learns node representation features for networks with three types of node entities. We argue that tripartite networks are common in real world applications, and the essential challenge of the representation learning is the heterogeneous relations between
Gharibshah, Zhabiz, Zhu, Xingquan
openaire +2 more sources
Molecular Oncology, EarlyView.Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee +8 more
wiley +1 more source
Analyzing Input and Output Representations for Speech-Driven Gesture Generation
, 2019 This paper presents a novel framework for automatic speech-driven gesture generation, applicable to human-agent interaction including both virtual agents and robots.
Boersma Paul +6 more
core +1 more source