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Hybrid Nanofibers for Multimodal Accelerated Wound Healing
Advanced Healthcare Materials, EarlyView.Fabrication of wound healing scaffolds based on biocompatible nanofibers. Nanofibers offering high surface area, flexibility, and biocompatibility significantly improved the healing outcome in vivo. Histological, immunological, and anti‐inflammatory markers are noticeably better in treated wounds.
Viraj P. Nirwan +15 more
wiley +1 more source
Advanced Healthcare Materials, EarlyView.We developed a novel copper‐doped aluminum nano‐adjuvant (CuNA) to overcome cytarabine resistance in acute myeloid leukemia (AML). CuNA effectively sensitizes drug‐resistant AML cells to cytarabine by inducing mitochondrial dysfunction and inhibiting HMGCR/GPX4 to amplify ferroptosis.
Chao He +10 more
wiley +1 more source
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Mesochronal Structure Learning
Uncertainty in artificial intelligence : proceedings of the ... conference. Conference on Uncertainty in Artificial Intelligence, 2015Standard time series structure learning algorithms assume that the measurement timescale is approximately the same as the timescale of the underlying (causal) system. In many scientific contexts, however, this assumption is violated: the measurement timescale can be substantially slower than the system timescale (so intermediate time series datapoints ...
Sergey, Plis, David, Danks, Jianyu, Yang
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2022
This report documents the program and the outcomes of Dagstuhl Seminar 21362 "Structure and Learning", held from September 5 to 10, 2021. Structure and learning are among the most prominent topics in Artificial Intelligence (AI) today. Integrating symbolic and numeric inference was set as one of the next open AI problems at the Townhall meeting "A 20 ...
Dong, Tiansi +4 more
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This report documents the program and the outcomes of Dagstuhl Seminar 21362 "Structure and Learning", held from September 5 to 10, 2021. Structure and learning are among the most prominent topics in Artificial Intelligence (AI) today. Integrating symbolic and numeric inference was set as one of the next open AI problems at the Townhall meeting "A 20 ...
Dong, Tiansi +4 more
openaire +1 more source
On Learning Decision Structures
Fundamenta Informaticae, 1997A decision structure is a simple and powerful tool for organizing a decision process. It differs from a conventional decision tree in that its nodes are assigned tests that can be functions of the attributes, rather than single attributes; the branches stemming from a node can be assigned a subset of attribute values rather than a single attribute ...
Imam, Ibrahim F., Michalski, Ryszard S.
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Current Directions in Psychological Science, 2020
Social-structure learning is the process by which social groups are identified on the basis of experience. Building on models of structure learning in other domains, we formalize this problem within a Bayesian framework. According to this framework, the probabilistic assignment of individuals to groups is computed by combining information about ...
Samuel J. Gershman, Mina Cikara
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Social-structure learning is the process by which social groups are identified on the basis of experience. Building on models of structure learning in other domains, we formalize this problem within a Bayesian framework. According to this framework, the probabilistic assignment of individuals to groups is computed by combining information about ...
Samuel J. Gershman, Mina Cikara
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Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020
We present Neural Structured Learning (NSL) in TensorFlow [2], a new learning paradigm to train neural networks by leveraging structured signals in addition to feature inputs. Structure can be explicit as represented by a graph, or implicit, either induced by adversarial perturbation or inferred using techniques like embedding learning.
Arjun Gopalan +7 more
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We present Neural Structured Learning (NSL) in TensorFlow [2], a new learning paradigm to train neural networks by leveraging structured signals in addition to feature inputs. Structure can be explicit as represented by a graph, or implicit, either induced by adversarial perturbation or inferred using techniques like embedding learning.
Arjun Gopalan +7 more
openaire +1 more source