deep reinforcement learning Search Results


90
BioMimetic Therapeutics network deep reinforcement learning (n-drl) framework
Network Deep Reinforcement Learning (N Drl) Framework, supplied by BioMimetic Therapeutics, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Syscon Inc deep reinforcement learning
Deep Reinforcement Learning, supplied by Syscon Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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IEEE Access deep reinforcement learning model
Deep Reinforcement Learning Model, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Dornheim Medical Images deep reinforcement learning algorithm
Deep Reinforcement Learning Algorithm, supplied by Dornheim Medical Images, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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LAVET Pharmaceuticals Ltd reinforcement learning
<t>Reinforcement</t> Learning (François-Lavet et al. )
Reinforcement Learning, supplied by LAVET Pharmaceuticals Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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IEEE Access deep reinforcement learning tf-agent-based object tracking with virtual autonomous drone in a game engine
<t>Reinforcement</t> Learning (François-Lavet et al. )
Deep Reinforcement Learning Tf Agent Based Object Tracking With Virtual Autonomous Drone In A Game Engine, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Graduate Aerospace Laboratories deep reinforcement learning
<t>Reinforcement</t> Learning (François-Lavet et al. )
Deep Reinforcement Learning, supplied by Graduate Aerospace Laboratories, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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IEEE Access deep reinforcement learning
<t>Reinforcement</t> Learning (François-Lavet et al. )
Deep Reinforcement Learning, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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IEEE Access robust deep reinforcement learning
<t>Reinforcement</t> Learning (François-Lavet et al. )
Robust Deep Reinforcement Learning, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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KU Leuven stability analysis and performance improvement of deep reinforcement learning algorithms
<t>Reinforcement</t> Learning (François-Lavet et al. )
Stability Analysis And Performance Improvement Of Deep Reinforcement Learning Algorithms, supplied by KU Leuven, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Preferred Networks Inc deep reinforcement learning
<t>Reinforcement</t> Learning (François-Lavet et al. )
Deep Reinforcement Learning, supplied by Preferred Networks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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AstraZeneca ltd deep reinforcement learning based molecular de novo design method
( A ) The identification of ten commercial-accessible aromatic fragments aided by deep <t>reinforcement</t> learning model; ( B ) Synthesis of LFS-1107 via the installation of aromatic tetrazole moiety selected from the previous step to the sulforaphene parent structure; ( C ) Assessment of protein-ligand binding kinetics and binding affinity of tetrazole aromatic fragments via Bio-layer interferometry (BLI) assay; ( D ) Binding affinity of LFS-1107 and KPT-330 determined via BLI assay: LFS-1107, K d ~1.25E-11 M; KPT-330: K d ~5.29E-09 M. Figure 1—source data 1. The chemical structure of 10 commercial-accessible aromatic fragments. Figure 1—source data 2. The synthesis of compound LFS-1107. Figure 1—source data 3. The data of affinities and binding kinetics of CRM1 to S5 and S8. Figure 1—source data 4. The data of affinities and binding kinetics of CRM1 to LFS-1107 and KPT-330.
Deep Reinforcement Learning Based Molecular De Novo Design Method, supplied by AstraZeneca ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/deep+reinforcement+learning/pmc10637774-108-8-21?v=AstraZeneca+ltd
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deep reinforcement learning based molecular de novo design method - by Bioz Stars, 2026-08
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Image Search Results


Reinforcement Learning (François-Lavet et al. )

Journal: Artificial Intelligence Review

Article Title: Deep learning in the stock market—a systematic survey of practice, backtesting, and applications

doi: 10.1007/s10462-022-10226-0

Figure Lengend Snippet: Reinforcement Learning (François-Lavet et al. )

Article Snippet: Fig. 13 Reinforcement Learning (François-Lavet et al. ) It is common to see a RL system formulated as a Markov decision process Markov decision process (MDP) in which the system is fully observable, i.e., the state of the environment is the same as the observation that the agent perceives (François-Lavet et al. ).

Techniques:

Journal: Artificial Intelligence Review

Article Title: Deep learning in the stock market—a systematic survey of practice, backtesting, and applications

doi: 10.1007/s10462-022-10226-0

Figure Lengend Snippet:

Article Snippet: Fig. 13 Reinforcement Learning (François-Lavet et al. ) It is common to see a RL system formulated as a Markov decision process Markov decision process (MDP) in which the system is fully observable, i.e., the state of the environment is the same as the observation that the agent perceives (François-Lavet et al. ).

Techniques: Plasmid Preparation

( A ) The identification of ten commercial-accessible aromatic fragments aided by deep reinforcement learning model; ( B ) Synthesis of LFS-1107 via the installation of aromatic tetrazole moiety selected from the previous step to the sulforaphene parent structure; ( C ) Assessment of protein-ligand binding kinetics and binding affinity of tetrazole aromatic fragments via Bio-layer interferometry (BLI) assay; ( D ) Binding affinity of LFS-1107 and KPT-330 determined via BLI assay: LFS-1107, K d ~1.25E-11 M; KPT-330: K d ~5.29E-09 M. Figure 1—source data 1. The chemical structure of 10 commercial-accessible aromatic fragments. Figure 1—source data 2. The synthesis of compound LFS-1107. Figure 1—source data 3. The data of affinities and binding kinetics of CRM1 to S5 and S8. Figure 1—source data 4. The data of affinities and binding kinetics of CRM1 to LFS-1107 and KPT-330.

Journal: eLife

Article Title: Discovery and biological evaluation of a potent small molecule CRM1 inhibitor for its selective ablation of extranodal NK/T cell lymphoma

doi: 10.7554/eLife.80625

Figure Lengend Snippet: ( A ) The identification of ten commercial-accessible aromatic fragments aided by deep reinforcement learning model; ( B ) Synthesis of LFS-1107 via the installation of aromatic tetrazole moiety selected from the previous step to the sulforaphene parent structure; ( C ) Assessment of protein-ligand binding kinetics and binding affinity of tetrazole aromatic fragments via Bio-layer interferometry (BLI) assay; ( D ) Binding affinity of LFS-1107 and KPT-330 determined via BLI assay: LFS-1107, K d ~1.25E-11 M; KPT-330: K d ~5.29E-09 M. Figure 1—source data 1. The chemical structure of 10 commercial-accessible aromatic fragments. Figure 1—source data 2. The synthesis of compound LFS-1107. Figure 1—source data 3. The data of affinities and binding kinetics of CRM1 to S5 and S8. Figure 1—source data 4. The data of affinities and binding kinetics of CRM1 to LFS-1107 and KPT-330.

Article Snippet: In the present study, we adopted the deep reinforcement learning based molecular de novo design method developed by Olivecrona etc. from AstraZeneca.

Techniques: Ligand Binding Assay, Binding Assay