Results 81 to 90 of about 41,144 (258)

Streamlining Prediction in Bayesian Deep Learning

CoRR
Peer ...
Solin Arno, Trapp Martin, Klasson Marcus, Li Rui   +3 more
openaire   +5 more sources

Advanced Manufacturing of Composite‐Based Systems for Energy Applications

Advanced Materials Technologies, EarlyView.
Advanced manufacturing enables the integration of polymers, ceramics, metal oxides, and composites into architected microstructures with tailored transport pathways. By coupling material selection, manufacturing strategy, and structural design, multifunctional energy systems can simultaneously improve electrochemical performance, thermal management ...
Sri Vaishnavi Thummalapalli, Dhanush Patil, Libin Yang, M. Taylor Sobczak, Anshul Kulkarni, Xiao Sun, Arunachalam Ramanathan, Tiantian Li, Ramaraja P. Ramasamy, Jason J. Locklin, Yanyu Chen, Xianqiao Wang, Arunachala Mada Kannan, Kenan Song   +13 more
wiley   +1 more source

Deep Bayesian Active Learning with Image Data

CoRR, 2017
Even though active learning forms an important pillar of machine learning, deep learning tools are not prevalent within it. Deep learning poses several difficulties when used in an active learning setting. First, active learning (AL) methods generally rely on being able to learn and update models from small amounts of data.
Gal, Y, Islam, R, Ghahramani, Z
openaire   +4 more sources

On‐Chip Photonic Neural Network Architectures

Advanced Optical Materials, EarlyView.
This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong, Berkay Neseli, Seungyeon Cho, Seungsoo Lee, Yeonjun Kim, Seungyoon Choi, Hyo‐Hoon Park, Hamza Kurt   +7 more
wiley   +1 more source

Bayesian Deep Learning for Discrete Choice

Discrete choice models (DCMs) are used to analyze individual decision-making in contexts such as transportation choices, political elections, and consumer preferences. DCMs play a central role in applied econometrics by enabling inference on key economic variables, such as marginal rates of substitution, rather than focusing solely on predicting ...
Daniel F. Villarraga, Ricardo A. Daziano
openaire   +3 more sources

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source

How to beat a Bayesian adversary

European Journal of Applied Mathematics
Deep neural networks and other modern machine learning models are often susceptible to adversarial attacks. Indeed, an adversary may often be able to change a model’s prediction through a small, directed perturbation of the model’s input – an issue in ...
Zihan Ding, Kexin Jin, Jonas Latz, Chenguang Liu   +3 more
doaj   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Compliant Pneumatic Feet with Real‐Time Stiffness Adaptation for Humanoid Locomotion

Advanced Robotics Research, EarlyView.
A compliant pneumatic foot with real‐time variable stiffness enables humanoid robots to adapt to changing terrains. Using onboard vision and pressure control, the foot modulates stiffness within each gait cycle, reducing impact forces and improving balance. The design, cast in soft silicone with embedded air chambers and Kevlar wrapping, offers durable,
Irene Frizza, Hiroshi Kaminaga, Philippe Fraisse, Gentiane Venture   +3 more
wiley   +1 more source

Muscle Control of an Extra Robotic Digit

Advanced Robotics Research, EarlyView.
This study compares muscle‐ and movement‐based control for operating a supernumerary robotic thumb. While movement control performs better in the proposed tasks, muscle‐based (EMG) control promotes broader motor learning. The results highlight the promise and challenges of using biosignals for human augmentation, offering new insights into intuitive ...
Julien Russ, Lucy Dowdall, Francesco Cenciarelli, Kitty Goodridge, Mabel Ziman, Hristo Dimitrov, Danielle Clode, Tamar R. Makin   +7 more
wiley   +1 more source