SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3051–3100 of 4891 papers

TitleStatusHype
Dynamic Voxel Grid Optimization for High-Fidelity RGB-D Supervised Surface Reconstruction—0
DynamicDet: A Unified Dynamic Architecture for Object DetectionCode1
Gradient-Free Textual Inversion—0
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot LearningCode1
State estimation of a carbon capture process through POD model reduction and neural network approximation—0
Scale-Space Hypernetworks for Efficient Biomedical Imaging—0
Machine learning for structure-property relationships: Scalability and limitations—0
A Unified Framework for Exploratory Learning-Aided Community Detection Under Topological Uncertainty—0
A Framework for Combustion Chemistry Acceleration with DeepONets—0
One Transform To Compute Them All: Efficient Fusion-Based Full-Reference Video Quality Assessment—0
Visualizing Skiers' Trajectories in Monocular Videos—0
When approximate design for fast homomorphic computation provides differential privacy guarantees—0
InterFormer: Real-time Interactive Image SegmentationCode1
Efficient CNNs via Passive Filter Pruning—0
Tractable Identification of Electric Distribution Networks—0
A differentiable programming framework for spin modelsCode0
Generative Multiplane Neural Radiance for 3D-Aware Image GenerationCode1
Not All Features Matter: Enhancing Few-shot CLIP with Adaptive Prior RefinementCode1
On Degeneracy Issues in Multi-parametric Programming and Critical Region Exploration based Distributed Optimization in Smart Grid Operations—0
Propagating Parameter Uncertainty in Power System Nonlinear Dynamic Simulations Using a Koopman Operator-Based Surrogate Model—0
Polarity is all you need to learn and transfer fasterCode0
Efficient Alternating Minimization Solvers for Wyner Multi-View Unsupervised LearningCode0
On the Importance of Feature Separability in Predicting Out-Of-Distribution Error—0
GP-PCS: One-shot Feature-Preserving Point Cloud Simplification with Gaussian Processes on Riemannian ManifoldsCode0
Heat flux for semi-local machine-learning potentialsCode1
EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level LatenciesCode2
Marching-Primitives: Shape Abstraction from Signed Distance FunctionCode1
NVAutoNet: Fast and Accurate 360^ 3D Visual Perception For Self Driving—0
Revisiting DeepFool: generalization and improvementCode0
Hardness of Independent Learning and Sparse Equilibrium Computation in Markov Games—0
A Novel and Optimal Spectral Method for Permutation Synchronization—0
GNN-Assisted Phase Space Integration with Application to Atomistics—0
Optimized preprocessing and Tiny ML for Attention State Classification—0
SIESTA: Efficient Online Continual Learning with SleepCode1
FD-Net: An Unsupervised Deep Forward-Distortion Model for Susceptibility Artifact Correction in EPICode0
XVoxel-Based Parametric Design Optimization of Feature Models—0
A Spatio-temporal Decomposition Method for the Coordinated Economic Dispatch of Integrated Transmission and Distribution Grids—0
HDformer: A Higher Dimensional Transformer for Diabetes Detection Utilizing Long Range Vascular Signals—0
Robust Mode Connectivity-Oriented Adversarial Defense: Enhancing Neural Network Robustness Against Diversified _p AttacksCode1
All4One: Symbiotic Neighbour Contrastive Learning via Self-Attention and Redundancy ReductionCode0
Active Semi-Supervised Learning by Exploring Per-Sample Uncertainty and Consistency—0
BiFormer: Vision Transformer with Bi-Level Routing AttentionCode2
Interpretable Ensembles of Hyper-Rectangles as Base ModelsCode0
Optimal Sampling Designs for Multi-dimensional Streaming Time Series with Application to Power Grid Sensor Data—0
Gradient-Descent Based Optimization of Constant Envelope OFDM Waveforms—0
Dynamic Clustering and Cluster Contrastive Learning for Unsupervised Person Re-identificationCode1
Importance Filtering with Risk Models for Complex Driving Situations—0
NeurEPDiff: Neural Operators to Predict Geodesics in Deformation Spaces—0
BCSSN: Bi-direction Compact Spatial Separable Network for Collision Avoidance in Autonomous Driving—0
A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph DataCode4
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified