Results 81 to 90 of about 3,000 (250)

Deep Reinforcement Learning‐Based Control for Real‐Time Hybrid Simulation of Civil Structures

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Real‐time Hybrid Simulation (RTHS) is a cyber‐physical technique that studies the dynamic behavior of a system by combining physical and numerical components that are coupled through a boundary condition enforcer. In structural engineering, the numerical components are subjected to environmental loads that become dynamic displacements of the ...
Andrés Felipe Niño, Alejandro Palacio‐Betancur, Piedad Miranda‐Chiquito, Juan David Amaya, Christian E. Silva, Mariantonieta Gutierrez Soto, Luis Felipe Giraldo   +6 more
wiley   +1 more source

Sentipensar [Feel‐Thinking] Cultivates Collective Scientific Sensemaking and Worldbuilding Within and Beyond Ecological Despair

Science Education, EarlyView.
ABSTRACT Educating youth about environmental and climate justice is crucial in realizing a sustainable and flourishing future. Yet this can be challenging given the intense eco‐emotions youth experience and express while learning about these consequential realities and their implications.
Kelsie Fowler
wiley   +1 more source

LaGu-RCL: Language-Guided Resolution-Continual Learning for Semantic Segmentation of Remote Sensing Images

Remote Sensing
Remote sensing image semantic segmentation faces substantial challenges in training and transferring models across images with varying resolutions. This issue can be effectively mitigated by continuously learning knowledge derived from new resolutions ...
Penglong Li, Zezhong Ma, Haifeng Li, Zhenyang Huang   +3 more
doaj   +1 more source

Predicting the Susceptibility of Examples to Catastrophic Forgetting

Catastrophic forgetting - the tendency of neural networks to forget previously learned data when learning new information - remains a central challenge in continual learning. In this work, we adopt a behavioral approach, observing a connection between learning speed and forgetting: examples learned more quickly are less prone to forgetting. Focusing on
Guy Hacohen, Tinne Tuytelaars
openaire   +3 more sources

Overcoming catastrophic forgetting in neural networks

CoRR
Catastrophic forgetting is the primary challenge that hinders continual learning, which refers to a neural network ability to sequentially learn multiple tasks while retaining previously acquired knowledge. Elastic Weight Consolidation, a regularization-based approach inspired by synaptic consolidation in biological neural systems, has been used to ...
Brandon Shuen Yi Loke, Filippo Quadri, Gabriel Vivanco, Maximilian Casagrande, Saúl Fenollosa   +4 more
openaire   +2 more sources

National Policy Coherence Counts for Reducing Inequality in Global Climate and Development Agendas

Sustainable Development, EarlyView.
ABSTRACT International institutions promote policy coherence as crucial to the effective and fair implementation of global sustainability agendas, though the evidence for its benefits is slim. We present here the first systematic cross‐country dataset on the consequences of national government efforts to promote policy coherence for vulnerable groups ...
Katherine Browne, Adis Dzebo, Zoha Shawoo, Mario Cardenas, Pierrick Chalaye, Alexia Faus Onbargi, Cassilde Muhoza, Patricia Nicdao, Nokwethaba Makhanya, Navam Niles, Priyatma Singh   +10 more
wiley   +1 more source

Continual Test-Time Adaptation for Robust Remote Photoplethysmography Estimation

IEEE Access
Remote photoplethysmography (rPPG) estimation has made considerable progress by leveraging deep learning, yet its performance remains highly susceptible to the domain shifts caused by lighting, skin tone and movement, particularly during inference ...
Hyunwoo Lee, Haechang Lee, Byung Hyun Lee, Se Young Chun   +3 more
doaj   +1 more source

Living Through a Changing Climate: Stress, Trauma, and Gendered Resilience Among Women in Coastal and Northern Ghana

Sustainable Development, EarlyView.
ABSTRACT Climate change is reshaping everyday life in Ghana through coastal erosion, flooding, erratic rainfall, water scarcity, extreme heat, and agricultural insecurity. This study examines how these changes produce stress, trauma, and gendered resilience among women in Salakope and Choggu Yapalsi, two climate‐vulnerable communities in coastal and ...
Jacob Kwakye
wiley   +1 more source

Conditions for Catastrophic Forgetting in Multilingual Translation

Proceedings of the 5th Workshop on Multilingual Representation Learning (MRL 2025)
Fine-tuning multilingual foundation models on specific languages often induces catastrophic forgetting, degrading performance on languages unseen in fine-tuning. While this phenomenon is widely-documented, the literature presents fragmented results about when forgetting occurs.
Danni Liu, Jan Niehues
openaire   +2 more sources

Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning

SmartBot, EarlyView.
Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo, Rodrigo S. Jamisola Jr., Molaletsa Namoshe   +2 more
wiley   +1 more source