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 1326–1350 of 4891 papers

TitleStatusHype
NeRF and Gaussian Splatting SLAM in the WildCode1
Granular Ball Twin Support Vector Machine with Universum Data—0
Many-MobileNet: Multi-Model Augmentation for Robust Retinal Disease ClassificationCode2
Optimized CNNs for Rapid 3D Point Cloud Object Recognition—0
Comparative Analysis of Multi-Agent Reinforcement Learning Policies for Crop Planning Decision Support—0
Gracefully Filtering Backdoor Samples for Generative Large Language Models without RetrainingCode1
Real-time Traffic Simulation and Management for Large-scale Urban Air Mobility: Integrating Route Guidance and Collision Avoidance—0
Iterative Distributed Multinomial RegressionCode0
RILQ: Rank-Insensitive LoRA-based Quantization Error Compensation for Boosting 2-bit Large Language Model AccuracyCode0
Fire-Image-DenseNet (FIDN) for predicting wildfire burnt area using remote sensing data—0
Fréchet Radiomic Distance (FRD): A Versatile Metric for Comparing Medical Imaging DatasetsCode1
CSP-AIT-Net: A contrastive learning-enhanced spatiotemporal graph attention framework for short-term metro OD flow prediction with asynchronous inflow tracking—0
How Much Can Time-related Features Enhance Time Series Forecasting?Code1
Bridging Fairness Gaps: A (Conditional) Distance Covariance Perspective in Fairness Learning—0
DSSRNN: Decomposition-Enhanced State-Space Recurrent Neural Network for Time-Series AnalysisCode0
2DMamba: Efficient State Space Model for Image Representation with Applications on Giga-Pixel Whole Slide Image ClassificationCode2
Dynamic Token Selection for Aerial-Ground Person Re-Identification—0
Nonlinearity and Uncertainty Informed Moment-Matching Gaussian Mixture SplittingCode0
QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities—0
Distributed Differentially Private Data Analytics via Secure Sketching—0
HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks—0
Hyperspectral Images Efficient Spatial and Spectral non-Linear Model with Bidirectional Feature Learning—0
Wafer2Spike: Spiking Neural Network for Wafer Map Pattern ClassificationCode0
Materials Learning Algorithms (MALA): Scalable Machine Learning for Electronic Structure Calculations in Large-Scale Atomistic Simulations—0
L4acados: Learning-based models for acados, applied to Gaussian process-based predictive controlCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified