Results 81 to 90 of about 451,604 (277)

Adversarial Incremental Learning

, 2020
Although deep learning performs really well in a wide variety of tasks, it still suffers from catastrophic forgetting -- the tendency of neural networks to forget previously learned information upon learning new tasks where previous data is not available.
openaire   +2 more sources

3D (Bio) Printing Combined Fiber Fabrication Methods for Tissue Engineering Applications: Possibilities and Limitations

Advanced Functional Materials, EarlyView.
Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana, Indra Apsite, Leonid Ionov   +2 more
wiley   +1 more source

S²IL: Structurally Stable Incremental Learning

IEEE Access
Feature Distillation (FD) strategies are proven to be effective in mitigating Catastrophic Forgetting (CF) seen in Class Incremental Learning (CIL).
S. Balasubramanian, P. Yedu Krishna, Talasu Sai Sriram, M. Sai Subramaniam, Manepalli Pranav Phanindra Sai, Ravi Mukkamala   +5 more
doaj   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Incremental Online Learning in High Dimensions [PDF]

Neural Computation, 2005
Locally weighted projection regression (LWPR) is a new algorithm for incremental nonlinear function approximation in high-dimensional spaces with redundant and irrelevant input dimensions. At its core, it employs nonparametric regression with locally linear models.
Vijayakumar, Sethu, D'Souza, Aaron, Schaal, Stefan   +2 more
openaire   +4 more sources

Electroactive Metal–Organic Frameworks for Electrocatalysis

Advanced Functional Materials, EarlyView.
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska, Yutong Luo, Ruyan Zhao, Jianjun Zhang, Mingchao Wang, Xinliang Feng, Eike Brunner, Stefan Kaskel   +7 more
wiley   +1 more source

Efficient Incremental Learning Using Dynamic Correction Vector

IEEE Access, 2020
One major challenge for modern artificial neural networks (ANNs) is that they typically does not handle incremental learning well. In other words, while learning the new features, the performances of existing features usually deteriorate. This phenomenon
Yun Xiang, Yongbiao Miao, Jingyin Chen, Qi Xuan   +3 more
doaj   +1 more source

Formation of Stable Amorphous Calcium Phosphate and Collagen Assemblies by a Versatile Spray‐Drying Approach

Advanced Functional Materials, EarlyView.
Amorphous calcium phosphate (ACP) microparticles with long‐term and thermal stability are prepared with or without collagen using a scalable one‐pot spray‐drying process. Under simulated physiological conditions, they crystallize into biomimetic bone mineral and, when combined with collagen, form extrudable, fibrillar bone‐like 3D constructs.
Camila Bussola Tovani, Nessma Bennaceur, Celina Benkhellat, Tristan Georges, Clara Doisneau, Vaskar Sardhalia, Thierry Azaïs, Flora Lemaire, Halima Kerdjoudj, Mohamed Selmane, Capucine Sassoye, Marie Albéric, Cédric Boissière, Nadine Nassif   +13 more
wiley   +1 more source

Incremental Prototype Tuning for Class Incremental Learning

, 2022
Class incremental learning(CIL) has attracted much attention, but most existing related works focus on fine-tuning the entire representation model, which inevitably results in much catastrophic forgetting. In the contrast, with a semantic-rich pre-trained representation model, parameter-additional-tuning (PAT) only changes very few parameters to learn ...
Deng, Jieren, Hu, Jianhua, Zhang, Haojian, Wang, Yunkuan   +3 more
openaire   +2 more sources

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

Advanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi, Sumukh Shankar Sharadaprasad, Rochus Schmid   +2 more
wiley   +1 more source