Micro-drones can be integrated into various industrial applications but are constrained by their computing power and expert pilots, a secondary challenge. This study presents a computationally-efficient deep convolutional neural network that utilizes...
Plate and spring reverberators are electromechanical systems first used and researched as means to substitute real room reverberation. Nowadays they are often used in music production for aesthetic reasons due to their particular sonic characteristic...
The paper presents a study of an adaptive approach to lateral skew control for an experimental railway stand. The preliminary experiments with the real experimental railway stand and simulations with its 3-D mechanical model, indicates difficulties o...
We present Joey NMT, a minimalist neural machine translation toolkit based on PyTorch that is specifically designed for novices. Joey NMT provides many popular NMT features in a small and simple code base, so that novices can easily and quickly learn...
Neyman-Scott processes (NSPs) are point process models that generate clusters of points in time or space. They are natural models for a wide range of phenomena, ranging from neural spike trains to document streams. The clustering property is achieved...
This paper studies a multi-task control problem where multiple linear systems are to be regulated by a single non-linear controller. In particular, motivated by recent advances in multi-task learning and the design of brain-inspired architectures, we...
We propose a neural network architecture for learning vector representations of hotels. Unlike previous works, which typically only use user click information for learning item embeddings, we propose a framework that combines several sources of data,...
We present a hybrid neuro-symbolic system for the SemEval-2026 Task 4 on Narrative Story Similarity. Our approach combines neural self-consistency voting with a novel Multi-Scale Narrative Analysis Ensemble that operates as a symbolic tiebreaker. The...
In the era of the knowledge economy, understanding how job skills influence salary is crucial for promoting recruitment with competitive salary systems and aligned salary expectations. Despite efforts on salary prediction based on job positions and t...
Skin cancer is by far the most common type of cancer. Early detection is the key to increase the chances for successful treatment significantly. Currently, Deep Neural Networks are the state-of-the-art results on automated skin cancer classification....
Feb 19, 2026 · A new soft robotic arm can safely operate close to the human body without causing discomfort or injury. The AI control system is well-suited for assistive scenarios like showering, where …
simulate reality could be applied to real world settings. In 2022, Yann LeCun saw a world model (defined by him as a neural network that acts as a mental
Final project for Dr. Steve Chase's Neural Data Analysis class. The final product is a MATLAB GUI that allows users to manipulate parameters and observe their effect on decoder accuracy. (⭐ 2)
Steven Chase uses brain-computer interfaces to study motor learning and skill acquisition. His work stands to provide a better understanding of how movement information is represented in networks of neurons in the brain and will inform the development of neural prosthetics.
explicit instructions. Within a subdiscipline of machine learning, advances in the field of deep learning have allowed neural networks, a class of statistical