Compression in 3D Gaussian Splatting: A Survey of Methods, Trends, and Future Directions

Feature-aware Hypergraph Generation via Next-Scale Prediction

GoDe: Gaussians on Demand for Progressive Level of Detail and Scalable Compression

Lightweight Embedded FPGA Deployment of Learned Image Compression with Knowledge Distillation and Hybrid Quantization

Memory Constrained Dynamic Subnetwork Update for Transfer Learning

Security and real-time fpga integration for learned image compression

The silence of the weights: an investigation of structural pruning strategies for attention-based audio signal architectures

NEPENTHE: Entropy-Based Pruning as a Neural Network Depth's Reducer

Efficient Resource-Constrained Training of Vision Transformers via Subspace Optimization

How I Met Your Bias: Investigating Bias Amplification in Diffusion Models

I-INR: Iterative Implicit Neural Representations

INSTANT: Compressing Gradients and Activations for Resource-Efficient Training

RAVE: Rate-Adaptive Visual Encoding for 3D Gaussian Splatting

Study of Training Dynamics for Memory-Constrained Fine-Tuning

Ask and Remember: A Questions-Only Replay Strategy for Continual Visual Question Answering

Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning

Capsule Networks Do Not Need to Model Everything

Denoising Diffusion Probabilistic Model for Point Cloud Compression at Low Bit-Rates

Diffusing DeBias: Synthetic Bias Amplification for Model Debiasing

Efficient adaptation of deep neural networks for semantic segmentation in space applications

Efficient Progressive Image Compression with Variance-aware Masking

ELMGS: Enhancing memory and computation scaLability through coMpression for 3D Gaussian Splatting

Enhancing Plasticity for First Session Adaptation Continual Learning

FOLDER: Accelerating Multi-modal Large Language Models with Enhanced Performance

HYGENE: A Diffusion-based Hypergraph Generation Method

Improving Generative Data Augmentation with Prior-Knowledge for Dysplasia Grading of Colorectal Polyps

LaCoOT: Layer Collapse through Optimal Transport

LayerFold: A Python library to reduce the depth of neural networks

Neural Velocity for hyperparameter tuning

Say My Name: a Model's Bias Discovery Framework

STanH: Parametric Quantization for Variable Rate Learned Image Compression

TEP-ones: A simple yet effective approach for transferability estimation of pruned backbones

Till the Layers Collapse: Compressing a Deep Neural Network Through the Lenses of Batch Normalization Layers

Unified Pipeline for Generalized Mental State Detection Using EEG Signals

WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarking

WiGNet: Windowed Vision Graph Neural Network

Activation Map Compression through Tensor Decomposition for Deep Learning

ALICE: Adapt your Learnable Image Compression modEl for variable bitrates

Boost Your NeRF: A Model-Agnostic Mixture of Experts Framework for High Quality and Efficient Rendering

Debiasing surgeon: fantastic weights and how to find them

Domain Adaptation for Learned Image Compression with Supervised Adapters

DSD$^2$: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free?

Find the Lady: Permutation and Re-Synchronization of Deep Neural Networks

Gabic: Graph-Based Attention Block for Image Compression

Memory-Optimized Once-For-All Network

Mini but Mighty: Finetuning ViTs with Mini Adapters

The Simpler The Better: An Entropy-Based Importance Metric To Reduce Neural Networks' Depth

Towards On-device Learning on the Edge: Ways to Select Neurons to Update under a Budget Constraint

Trimming the Fat: Efficient Compression of 3D Gaussian Splats through Pruning

Unsupervised Learning of Unbiased Visual Representations

Weighted Ensemble Models Are Strong Continual Learners

A Differentiable Entropy Model for Learned Image Compression

A hitchhiker's guide to white-box neural network watermarking robustness

AIoT-based Neural Decoding and Neurofeedback for Accelerated Cognitive Training: Vision, Directions and Preliminary Results

All predictions matter: an online video prediction approach

Can Unstructured Pruning Reduce the Depth in Deep Neural Networks?

Can we avoid Double Descent in Deep Neural Networks?

Compressing Explicit Voxel Grid Representations: Fast NeRFs Become Also Small

Disentangling private classes through regularization

Learn how to Prune Pixels for Multi-view Neural Image-based Synthesis

Mental State Classification Using EEG Signals: Ethics, Law and Challenges

Mental state classification using EEG signals: ethics, law and challenges

Mining bias-target Alignment from Voronoi Cells

Neural network-derived perfusion maps: A model-free approach to computed tomography perfusion in patients with acute ischemic stroke

Optimized preprocessing and Tiny ML for Attention State Classification

Packed Ensembles for efficient uncertainty estimation

SCoTTi: Save Computation at Training Time with an adaptive framework

Shannon strikes again! entropy-based pruning in deep neural networks for transfer learning under extreme memory and computation budgets

Sparse Double Descent in Vision Transformers: real or phantom threat?

Two is Better than One: Achieving High-Quality 3D Scene Modeling with a NeRF Ensemble

Unbiased Supervised Contrastive Learning

Unified Measures for the Rate-Distortion-Latency Trade-off

A Two-Step Radiologist-Like Approach for Covid-19 Computer-Aided Diagnosis from Chest X-Ray Images

Applications of AI and HPC in the Health Domain

Information Removal at the bottleneck in Deep Neural Networks

Loss-based sensitivity regularization: towards deep sparse neural networks

Marco Aldinucci, David Atienza, Federico Bolelli, Monica Caballero, Iacopo Colonnelli, Jose Flich, Jon A. Gomez, David Gonzalez, Costantino Grana, Marco Grangetto, Simone Leo, Pedro Lopez, Dana Oniga, Roberto Paredes, Luca Pireddu, Eduardo Quinones, Tatiana Silva

The DeepHealth HPC Infrastructure: Leveraging Heterogenous HPC and Cloud-Computing Infrastructures for IA-Based Medical Solutions

The DeepHealth Toolkit: A Key European Free and Open-Source Software for Deep Learning and Computer Vision Ready to Exploit Heterogeneous HPC and Cloud Architectures

The Rise of the Lottery Heroes: Why Zero-Shot Pruning is Hard

To update or not to update? Neurons at equilibrium in deep models

A Hitchhiker’s Guide towards Transactive Memory System Modeling in Small Group Interactions

Bridging the gap between debiasing and privacy for deep learning

Capsule Networks with Routing Annealing

Delving in the loss landscape to embed robust watermarks into neural networks

Dysplasia grading of colorectal polyps through convolutional neural network analysis of whole slide images

End: Entangling and disentangling deep representations for bias correction

HEMP: High-order entropy minimization for neural network compression

On the role of structured pruning for neural network compression

Serene: Sensitivity-based regularization of neurons for structured sparsity in neural networks

UniToPatho, a labeled histopathological dataset for colorectal polyps classification and adenoma dysplasia grading

A non-discriminatory approach to ethical deep learning

Pruning artificial neural networks: A way to find well-generalizing, high-entropy sharp minima

Unveiling covid-19 from chest x-ray with deep learning: a hurdles race with small data

Post-synaptic potential regularization has potential

Take a ramble into solution spaces for classification problems in neural networks

Learning sparse neural networks via sensitivity-driven regularization

Role of synaptic stochasticity in training low-precision neural networks

Communication scheduling and buslet synthesis for low-interconnect HLS designs

Method for learned image compression and related autoencoder

METHOD FOR ENHANCED IMAGE ENCODING AND DECODING USING A GRAPH-BASED ATTENTION BLOCK, AND RELATED ENCODER AND DECODER

METHOD FOR LEARNED IMAGE COMPRESSION AND RELATED AUTOENCODER

METHOD FOR LEARNED IMAGE DECOMPRESSION AND RELATED DECODER NETWORK AND DECODER-ENCODER ARCHITECTURE

METHOD FOR LEARNED IMAGE DECOMPRESSION AND RELATED DECODER NETWORK AND DECODER-ENCODER ARCHITECTURE

METHOD FOR REDUCING LATENCY IN VIDEO TRANSMISSION

METHOD FOR ENHANCED IMAGE ENCODING AND DECODING USING A GRAPH-BASED ATTENTION BLOCK, AND RELATED ENCODER AND DECODER

Method and apparatus for pruning neural networks

Neural networks having reduced number of parameters

UniTOBrain

UNITOPATHO