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Found 13 papers, 5 papers with code
Radio Map Estimation via Latent Domain Plug-and-Play Denoising
Unlike conventional PnP methods that operate directly in the data domain, the proposed method exploits the underlying physical structure of radio maps and proposes an ADMM algorithm that denoises in a latent domain.
Finite-volume method and observability analysis for core-shell enhanced single particle model for lithium iron phosphate batteries
The increasing adoption of Lithium Iron Phosphate (LFP) batteries in Electric Vehicles is driven by their affordability, abundant material supply, and safety advantages.
Comparing Mass-Preserving Numerical Methods for the Lithium-Ion Battery Single Particle Model
The single particle model (SPM) is a reduced electrochemical model that holds promise for applications in battery management systems due to its ability to accurately capture battery dynamics; however, the numerical discretization of the SPM requires careful consideration to ensure numerical stability and accuracy.
ASMR: Activation-sharing Multi-resolution Coordinate Networks For Efficient Inference
Coordinate network or implicit neural representation (INR) is a fast-emerging method for encoding natural signals (such as images and videos) with the benefits of a compact neural representation.
MOSEL: Inference Serving Using Dynamic Modality Selection
Rapid advancements over the years have helped machine learning models reach previously hard-to-achieve goals, sometimes even exceeding human capabilities.
Adversarial Self-Attack Defense and Spatial-Temporal Relation Mining for Visible-Infrared Video Person Re-Identification
In this work, the changes of views, posture, background and modal discrepancy are considered as the main factors that cause the perturbations of person identity features.
To Fold or Not to Fold: Graph Regularized Tensor Train for Visual Data Completion
Tensor train (TT) representation has achieved tremendous success in visual data completion tasks, especially when it is combined with tensor folding.
Overcoming Beam Squint in Dual-Wideband mmWave MIMO Channel Estimation: A Bayesian Multi-Band Sparsity Approach
A probabilistic model is built to induce the common sparsity in the spatial domain, and the first-order Taylor expansion is adopted to get rid of the grid mismatch in the dictionaries.
Low-rank Adaptation Method for Wav2vec2-based Fake Audio Detection
Self-supervised speech models are a rapidly developing research topic in fake audio detection.
Adaptive Fake Audio Detection with Low-Rank Model Squeezing
During the inference stage, these adaptation matrices are combined with the existing model to generate the final prediction output.
Detection of brain activations induced by naturalistic stimuli in a pseudo model-driven way
We evaluated the effectiveness of AINS with both statistical and predictive analyses on individual differences in sex and intelligence quotient (IQ), based on the four movie fMRI runs included in the Human Connectome Project dataset.
ADD 2022: the First Audio Deep Synthesis Detection Challenge
Audio deepfake detection is an emerging topic, which was included in the ASVspoof 2021.
Tensor Train Factorization and Completion under Noisy Data with Prior Analysis and Rank Estimation
Tensor train (TT) decomposition, a powerful tool for analyzing multidimensional data, exhibits superior performance in many machine learning tasks.
