Ramesh, Visvanathan

1. A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
   2020/09/03 by Martin Mundt, Mundt, Martin, Yongwon Hong +5 · 8 citations
   Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Multimodal Machine Learning Applications
2. Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset
   2019/04/02 by Mundt, Martin, Majumder, Sagnik, Murali, Sreenivas +2 · 2 citations
   #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
3. Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?
   2019/08/26 by Mundt, Martin, Pliushch, Iuliia, Majumder, Sagnik +1 · 2 citations
   #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
4. Designing a Hybrid Neural System to Learn Real-world Crack Segmentation from Fractal-based Simulation
   2023/09/18 by Achref Jaziri, Martin Mundt, Jaziri, Achref +5 · 4 citations
   Engineering · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Concrete Properties and Behavior #FOS: Computer and information sciences #Geotechnical Engineering and Underground Structures #Infrastructure Maintenance and Monitoring #Machine Learning (cs.LG)
5. When Deep Classifiers Agree: Analyzing Correlations between Learning Order and Image Statistics
   2021/05/19 by Iuliia Pliushch, Martin Mundt, Pliushch, Iuliia +5 · 2 citations
   Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural Networks and Applications
6. Model-driven Simulations for Deep Convolutional Neural Networks
   2016/05/31 by V. S. R. Veeravasarapu, Veeravasarapu, V S R, Constantin A. Rothkopf +3 · 2 citations
   Computer Science · Physics and Astronomy · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Human Pose and Action Recognition #Model Reduction and Neural Networks
7. Building effective deep neural network architectures one feature at a time
   2017/05/18 by Martin Mundt, Mundt, Martin, Tobias Weis +5 · 1 voice
   Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Domain Adaptation and Few-Shot Learning #cs.CV #cs.NE
8. A Procedural World Generation Framework for Systematic Evaluation of Continual Learning
   2021/06/04 by Timm Hess, Hess, Timm, Martin Mundt +5 · 1 citation
   Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Human Pose and Action Recognition #Machine Learning (cs.LG) #Video Surveillance and Tracking Methods
9. Mitigating the Stability-Plasticity Dilemma in Adaptive Train Scheduling with Curriculum-Driven Continual DQN Expansion
   2024/08/19 by Jaziri, Achref, Künzel, Etienne, Ramesh, Visvanathan · 2 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural and Evolutionary Computing (cs.NE)
10. Representation Learning in a Decomposed Encoder Design for Bio-inspired Hebbian Learning
    2023/11/22 by Achref Jaziri, Sina Ditzel, Jaziri, Achref +5 · 1 citation
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Cell Image Analysis Techniques #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE)