Artificial Neural Networks and Machine Learning - ICANN 2024
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Artificial Neural Networks and Machine Learning - ICANN 2024
33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17-20, 2024, Proceedings, Part X
Tetko, Igor V.; Malinovska, Kristina; Wand, Michael; Schmidhuber, Juergen
Springer International Publishing AG
11/2024
438
Mole
9783031723582
Pré-lançamento - envio 15 a 20 dias após a sua edição
Descrição não disponível.
.- Workshop: AI in Drug Discovery.
.- Combinatorial Library Neural Network (CoLiNN) for Combinatorial Library Visualization without Compound Enumeration.
.- De novo Drug Design - Do We Really Want To Be "Original"?
.- Elucidation of Molecular Substructures from Nuclear Magnetic Resonance Spectra using Gradient Boosting.
.- Neural SHAKE: Geometric Constraints in Graph Generative Models.
.- Scaffold Splits Overestimate Virtual Screening Performance.
.- Target-Aware Drug Activity Model: A deep learning approach to virtual HTS.
.- Workshop: Reservoir Computing.
.- Effects of Input Structure and Topology on Input-Driven Functional Connectivity Stability.
.- Non-dissipative Reservoir Computing approaches for time-series classification.
.- Onion Echo State Networks A Preliminary Analysis of Dynamics.
.- Oscillation-driven Reservoir Computing for Long-Term Replication of Chaotic Time Series.
.- Prediction of reaching movements with target information towards trans-humeral prosthesis control using Reservoir Computing and LSTMs.
.- Reducing Reservoir Dimensionality with Phase Space Construction for Simplified Hardware
Implementation.
.- Restricted Reservoirs on Heterogeneous Timescales.
.- Special Session: Accuracy, Stability, and Robustness in Deep Neural Networks.
.- Clean-image Backdoor Attacks.
.- MADE: A Universal Fine-tuning Framework to Enhance Robustness of Machine Reading Comprehension.
.- Robustness of biologically grounded neural networks against image perturbations.
.- Some Comparisons of Linear and Deep ReLU Network Approximation.
.- Unlearnable Examples Detection via Iterative Filtering.
.- Special Session: Neurorobotics.
.- Action recognition system integrating motion and object detection.
.- Active Vision for Physical Robots using the Free Energy Principle.
.- Learning Low-Level Causal Relations using a Simulated Robotic Arm.
.- Modular Reinforcement Learning In Long-Horizon Manipulation Tasks.
.- Robotic Model of the Mirror Neuron System: a Revival.
.- Self-organized attractoring in locomoting animals and robots: an emerging field.
.- Special Session: Spiking Neural Networks.
.- A Multi-modal Spiking Meta-learner With Brain-inspired Task-aware Modulation Scheme.
.- Event-Based Hand Detection on Neuromorphic Hardware Using a Sigma Delta Neural Network.
.- Learning in Recurrent Spiking Neural Networks with Sparse full-FORCE Training.
.- Natively neuromorphic LMU architecture for encoding-free SNN-based HAR on commercial edge devices.
.- Obtaining Optimal Spiking Neural Network in Sequence Learning via CRNN-SNN Conversion.
.- On Reducing Activity with Distillation and Regularization for Energy Ecient Spiking
Neural Networks.
.- Temporal Contrastive Learning for Spiking Neural
Networks.
.- Combinatorial Library Neural Network (CoLiNN) for Combinatorial Library Visualization without Compound Enumeration.
.- De novo Drug Design - Do We Really Want To Be "Original"?
.- Elucidation of Molecular Substructures from Nuclear Magnetic Resonance Spectra using Gradient Boosting.
.- Neural SHAKE: Geometric Constraints in Graph Generative Models.
.- Scaffold Splits Overestimate Virtual Screening Performance.
.- Target-Aware Drug Activity Model: A deep learning approach to virtual HTS.
.- Workshop: Reservoir Computing.
.- Effects of Input Structure and Topology on Input-Driven Functional Connectivity Stability.
.- Non-dissipative Reservoir Computing approaches for time-series classification.
.- Onion Echo State Networks A Preliminary Analysis of Dynamics.
.- Oscillation-driven Reservoir Computing for Long-Term Replication of Chaotic Time Series.
.- Prediction of reaching movements with target information towards trans-humeral prosthesis control using Reservoir Computing and LSTMs.
.- Reducing Reservoir Dimensionality with Phase Space Construction for Simplified Hardware
Implementation.
.- Restricted Reservoirs on Heterogeneous Timescales.
.- Special Session: Accuracy, Stability, and Robustness in Deep Neural Networks.
.- Clean-image Backdoor Attacks.
.- MADE: A Universal Fine-tuning Framework to Enhance Robustness of Machine Reading Comprehension.
.- Robustness of biologically grounded neural networks against image perturbations.
.- Some Comparisons of Linear and Deep ReLU Network Approximation.
.- Unlearnable Examples Detection via Iterative Filtering.
.- Special Session: Neurorobotics.
.- Action recognition system integrating motion and object detection.
.- Active Vision for Physical Robots using the Free Energy Principle.
.- Learning Low-Level Causal Relations using a Simulated Robotic Arm.
.- Modular Reinforcement Learning In Long-Horizon Manipulation Tasks.
.- Robotic Model of the Mirror Neuron System: a Revival.
.- Self-organized attractoring in locomoting animals and robots: an emerging field.
.- Special Session: Spiking Neural Networks.
.- A Multi-modal Spiking Meta-learner With Brain-inspired Task-aware Modulation Scheme.
.- Event-Based Hand Detection on Neuromorphic Hardware Using a Sigma Delta Neural Network.
.- Learning in Recurrent Spiking Neural Networks with Sparse full-FORCE Training.
.- Natively neuromorphic LMU architecture for encoding-free SNN-based HAR on commercial edge devices.
.- Obtaining Optimal Spiking Neural Network in Sequence Learning via CRNN-SNN Conversion.
.- On Reducing Activity with Distillation and Regularization for Energy Ecient Spiking
Neural Networks.
.- Temporal Contrastive Learning for Spiking Neural
Networks.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
artificial intelligence;classification;deep learning;generative models;graph neural networks;image processing;large language models;machine learning;neural networks;reinforcement learning;reservoir computing;robotics;spiking neural networks
.- Workshop: AI in Drug Discovery.
.- Combinatorial Library Neural Network (CoLiNN) for Combinatorial Library Visualization without Compound Enumeration.
.- De novo Drug Design - Do We Really Want To Be "Original"?
.- Elucidation of Molecular Substructures from Nuclear Magnetic Resonance Spectra using Gradient Boosting.
.- Neural SHAKE: Geometric Constraints in Graph Generative Models.
.- Scaffold Splits Overestimate Virtual Screening Performance.
.- Target-Aware Drug Activity Model: A deep learning approach to virtual HTS.
.- Workshop: Reservoir Computing.
.- Effects of Input Structure and Topology on Input-Driven Functional Connectivity Stability.
.- Non-dissipative Reservoir Computing approaches for time-series classification.
.- Onion Echo State Networks A Preliminary Analysis of Dynamics.
.- Oscillation-driven Reservoir Computing for Long-Term Replication of Chaotic Time Series.
.- Prediction of reaching movements with target information towards trans-humeral prosthesis control using Reservoir Computing and LSTMs.
.- Reducing Reservoir Dimensionality with Phase Space Construction for Simplified Hardware
Implementation.
.- Restricted Reservoirs on Heterogeneous Timescales.
.- Special Session: Accuracy, Stability, and Robustness in Deep Neural Networks.
.- Clean-image Backdoor Attacks.
.- MADE: A Universal Fine-tuning Framework to Enhance Robustness of Machine Reading Comprehension.
.- Robustness of biologically grounded neural networks against image perturbations.
.- Some Comparisons of Linear and Deep ReLU Network Approximation.
.- Unlearnable Examples Detection via Iterative Filtering.
.- Special Session: Neurorobotics.
.- Action recognition system integrating motion and object detection.
.- Active Vision for Physical Robots using the Free Energy Principle.
.- Learning Low-Level Causal Relations using a Simulated Robotic Arm.
.- Modular Reinforcement Learning In Long-Horizon Manipulation Tasks.
.- Robotic Model of the Mirror Neuron System: a Revival.
.- Self-organized attractoring in locomoting animals and robots: an emerging field.
.- Special Session: Spiking Neural Networks.
.- A Multi-modal Spiking Meta-learner With Brain-inspired Task-aware Modulation Scheme.
.- Event-Based Hand Detection on Neuromorphic Hardware Using a Sigma Delta Neural Network.
.- Learning in Recurrent Spiking Neural Networks with Sparse full-FORCE Training.
.- Natively neuromorphic LMU architecture for encoding-free SNN-based HAR on commercial edge devices.
.- Obtaining Optimal Spiking Neural Network in Sequence Learning via CRNN-SNN Conversion.
.- On Reducing Activity with Distillation and Regularization for Energy Ecient Spiking
Neural Networks.
.- Temporal Contrastive Learning for Spiking Neural
Networks.
.- Combinatorial Library Neural Network (CoLiNN) for Combinatorial Library Visualization without Compound Enumeration.
.- De novo Drug Design - Do We Really Want To Be "Original"?
.- Elucidation of Molecular Substructures from Nuclear Magnetic Resonance Spectra using Gradient Boosting.
.- Neural SHAKE: Geometric Constraints in Graph Generative Models.
.- Scaffold Splits Overestimate Virtual Screening Performance.
.- Target-Aware Drug Activity Model: A deep learning approach to virtual HTS.
.- Workshop: Reservoir Computing.
.- Effects of Input Structure and Topology on Input-Driven Functional Connectivity Stability.
.- Non-dissipative Reservoir Computing approaches for time-series classification.
.- Onion Echo State Networks A Preliminary Analysis of Dynamics.
.- Oscillation-driven Reservoir Computing for Long-Term Replication of Chaotic Time Series.
.- Prediction of reaching movements with target information towards trans-humeral prosthesis control using Reservoir Computing and LSTMs.
.- Reducing Reservoir Dimensionality with Phase Space Construction for Simplified Hardware
Implementation.
.- Restricted Reservoirs on Heterogeneous Timescales.
.- Special Session: Accuracy, Stability, and Robustness in Deep Neural Networks.
.- Clean-image Backdoor Attacks.
.- MADE: A Universal Fine-tuning Framework to Enhance Robustness of Machine Reading Comprehension.
.- Robustness of biologically grounded neural networks against image perturbations.
.- Some Comparisons of Linear and Deep ReLU Network Approximation.
.- Unlearnable Examples Detection via Iterative Filtering.
.- Special Session: Neurorobotics.
.- Action recognition system integrating motion and object detection.
.- Active Vision for Physical Robots using the Free Energy Principle.
.- Learning Low-Level Causal Relations using a Simulated Robotic Arm.
.- Modular Reinforcement Learning In Long-Horizon Manipulation Tasks.
.- Robotic Model of the Mirror Neuron System: a Revival.
.- Self-organized attractoring in locomoting animals and robots: an emerging field.
.- Special Session: Spiking Neural Networks.
.- A Multi-modal Spiking Meta-learner With Brain-inspired Task-aware Modulation Scheme.
.- Event-Based Hand Detection on Neuromorphic Hardware Using a Sigma Delta Neural Network.
.- Learning in Recurrent Spiking Neural Networks with Sparse full-FORCE Training.
.- Natively neuromorphic LMU architecture for encoding-free SNN-based HAR on commercial edge devices.
.- Obtaining Optimal Spiking Neural Network in Sequence Learning via CRNN-SNN Conversion.
.- On Reducing Activity with Distillation and Regularization for Energy Ecient Spiking
Neural Networks.
.- Temporal Contrastive Learning for Spiking Neural
Networks.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
