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Found 22 papers, 5 papers with code
Dissecting the Runtime Performance of the Training, Fine-tuning, and Inference of Large Language Models
For end users, our benchmark and findings help better understand different optimization techniques, training and inference frameworks, together with hardware platforms in choosing configurations for deploying LLMs.
A Monotonicity Constrained Attention Module for Emotion Classification with Limited EEG Data
In this work, a parameter-efficient attention module is presented for emotion classification using a limited, or relatively small, number of electroencephalogram (EEG) signals.
Physics Embedded Machine Learning for Electromagnetic Data Imaging
To benefit from prior knowledge in big data and the theoretical constraint of physical laws, physics embedded ML methods for EM imaging have become the focus of a large body of recent work.
Robust and accurate depth estimation by fusing LiDAR and Stereo
Because the density of the LiDAR data is relatively sparse on the y-axis, the converted disparity map is up-sampled using the interpolation method.
MusIAC: An extensible generative framework for Music Infilling Applications with multi-level Control
We present a novel music generation framework for music infilling, with a user friendly interface.
GANmouflage: 3D Object Nondetection with Texture Fields
Our model learns to camouflage a variety of object shapes from randomly sampled locations and viewpoints within the input scene, and is the first to address the problem of hiding complex object shapes.
Asynchronous Collaborative Localization by Integrating Spatiotemporal Graph Learning with Model-Based Estimation
In this paper, we introduce a novel approach that integrates uncertainty-aware spatiotemporal graph learning and model-based state estimation for a team of robots to collaboratively localize objects.
Solving Combined Field Integral Equation With Deep Neural Network for 2-D Conducting Object
Abstract—Solving the combined field integral equation (CFIE) for the large-scale scattering problem is computationally expensive.
Global Daily CO$_2$ emissions for the year 2020
That even substantial world-wide lockdowns of activity led to a one-time decline in global CO$_2$ emissions of only 5. 4% in one year highlights the significant challenges for climate change mitigation that we face in the post-COVID era.
Atmospheric and Oceanic Physics General Economics Economics
Multi-view Sensor Fusion by Integrating Model-based Estimation and Graph Learning for Collaborative Object Localization
Collaborative object localization aims to collaboratively estimate locations of objects observed from multiple views or perspectives, which is a critical ability for multi-agent systems such as connected vehicles.
Feature Sharing and Integration for Cooperative Cognition and Perception with Volumetric Sensors
In this paper, we examine the requirements, limitations, and performance of different cooperative perception techniques, and present an in-depth analysis of the notion of Deep Feature Sharing (DFS).
A variational autoencoder for music generation controlled by tonal tension
Many of the music generation systems based on neural networks are fully autonomous and do not offer control over the generation process.
Sound Symbolic Computation Audio and Speech Processing
Cooperative LIDAR Object Detection via Feature Sharing in Deep Networks
The recent advancements in communication and computational systems has led to significant improvement of situational awareness in connected and autonomous vehicles.
Graph Convolution Networks for Probabilistic Modeling of Driving Acceleration
The ability to model and predict ego-vehicle's surrounding traffic is crucial for autonomous pilots and intelligent driver-assistance systems.
Midi Miner -- A Python library for tonal tension and track classification
We present a Python library, called Midi Miner, that can calculate tonal tension and classify different tracks.
DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images
Current VHR(Very High Resolution) satellite images enable the detailed monitoring of the earth and can capture the ongoing works of railway construction.
SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception
SIGNet is shown to improve upon the state-of-the-art unsupervised learning for depth prediction by 30% (in squared relative error).
Ranked #62 on
Monocular Depth Estimation
on KITTI Eigen split
Multi-view Point Cloud Registration with Adaptive Convergence Threshold and its Application on 3D Model Retrieval
In this paper, we propose a framework to reconstruct the 3D models by the multi-view point cloud registration algorithm with adaptive convergence threshold, and subsequently apply it to 3D model retrieval.
Spatio-Temporal Road Scene Reconstruction using Superpixel Markov Random Field
The data fidelity term in the MRF's energy function is jointly computed according to the superpixel features of color, texture and location.
Driver Action Prediction Using Deep (Bidirectional) Recurrent Neural Network
In this paper, we formulate driver action prediction as a timeseries anomaly prediction problem.
Weighted Motion Averaging for the Registration of Multi-View Range Scans
With the overlapping percentage available, it views the overlapping percentage as the corresponding weight of each scan pair and proposes the weight motion averaging algorithm, which can pay more attention to reliable and accurate relative motions.
A Novel Artificial Fish Swarm Algorithm for Pattern Recognition with Convex Optimization
Among these parameters, visual and step are very significant in view of the fact that artificial fish basically move based on these parameters.
