{"total":31,"rows":[{"id":"2309.15426","title":"NeuRBF: A Neural Fields Representation with Adaptive Radial Basis Functions","created":"2023-09-27","cited_by_count":65,"area":null},{"id":"2310.06743","title":"Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks","created":"2023-10-10","cited_by_count":61,"area":null},{"id":"2312.02753","title":"C3: High-performance and low-complexity neural compression from a single image or video","created":"2023-12-05","cited_by_count":55,"area":null},{"id":"2301.09479","title":"Modality-Agnostic Variational Compression of Implicit Neural Representations","created":"2023-01-23","cited_by_count":22,"area":null},{"id":"2405.03376","title":"CRA5: Extreme Compression of ERA5 for Portable Global Climate and Weather Research via an Efficient Variational Transformer","created":"2024-05-06","cited_by_count":22,"area":null},{"id":"2401.11611","title":"Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks","created":"2024-01-21","cited_by_count":20,"area":null},{"id":"2306.05880","title":"Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations","created":"2023-06-09","cited_by_count":17,"area":null},{"id":"2302.00617","title":"Learning Large-scale Neural Fields via Context Pruned Meta-Learning","created":"2023-02-01","cited_by_count":13,"area":null},{"id":"2412.00505","title":"Good, Cheap, and Fast: Overfitted Image Compression with Wasserstein Distortion","created":"2024-11-30","cited_by_count":13,"area":null},{"id":"2503.01505","title":"Lossy Neural Compression for Geospatial Analytics: A Review","created":"2025-03-03","cited_by_count":10,"area":null},{"id":"2412.10153","title":"EVOS: Efficient Implicit Neural Training via EVOlutionary Selector","created":"2024-12-13","cited_by_count":7,"area":null},{"id":"2309.04037","title":"SRN-SZ: Deep Leaning-Based Scientific Error-bounded Lossy Compression with Super-resolution Neural Networks","created":"2023-09-07","cited_by_count":6,"area":null},{"id":"2412.09213","title":"Enhancing Implicit Neural Representations via Symmetric Power Transformation","created":"2024-12-12","cited_by_count":4,"area":null},{"id":"2402.05965","title":"Hybrid Neural Representations for Spherical Data","created":"2024-02-05","cited_by_count":3,"area":null},{"id":"2503.06623","title":"Transforming Weather Data from Pixel to Latent Space","created":"2025-03-09","cited_by_count":3,"area":null},{"id":"2503.15156","title":"ARC: Anchored Representation Clouds for High-Resolution INR Classification","created":"2025-03-19","cited_by_count":3,"area":null},{"id":"2511.15487","title":"NTK-Guided Implicit Neural Teaching","created":"2025-11-19","cited_by_count":2,"area":null},{"id":"2309.09002","title":"Earth Virtualization Engines -- A Technical Perspective","created":"2023-09-16","cited_by_count":1,"area":null},{"id":"2310.05691","title":"Climate-sensitive Urban Planning through Optimization of Tree Placements","created":"2023-10-09","cited_by_count":1,"area":null},{"id":"2404.18314","title":"DIRESA, a distance-preserving nonlinear dimension reduction technique based on regularized autoencoders","created":"2024-04-28","cited_by_count":1,"area":null},{"id":"2408.06486","title":"Implicit Neural Representation For Accurate CFD Flow Field Prediction","created":"2024-08-12","cited_by_count":1,"area":null},{"id":"2409.17367","title":"Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate Data","created":"2024-09-25","cited_by_count":1,"area":null},{"id":"2505.21658","title":"STACI: Spatio-Temporal Aleatoric Conformal Inference","created":"2025-05-27","cited_by_count":1,"area":null},{"id":"2301.02432","title":"Myths and Legends in High-Performance Computing","created":"2023-01-06","cited_by_count":0,"area":null},{"id":"2411.06155","title":"HiHa: Introducing Hierarchical Harmonic Decomposition to Implicit Neural Compression for Atmospheric Data","created":"2024-11-09","cited_by_count":0,"area":null},{"id":"2505.06316","title":"GraphComp: Extreme Error-bounded Compression of Scientific Data via Temporal Graph Autoencoders","created":"2025-05-08","cited_by_count":0,"area":null},{"id":"2506.08306","title":"AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data","created":"2025-06-10","cited_by_count":0,"area":null},{"id":"2506.15845","title":"Summary Statistics of Large-scale Model Outputs for Observation-corrected Outputs","created":"2025-06-18","cited_by_count":0,"area":null},{"id":"2510.23632","title":"LLMComp: A Language Modeling Paradigm for Error-Bounded Scientific Data Compression (Technical Report)","created":"2025-10-24","cited_by_count":0,"area":null},{"id":"2608.30262","title":"Multivariate Scientific Data Compression with Learned Cross-Variable Latent Decorrelation and Autoregressive Entropy Modeling","created":"2026-08-31","cited_by_count":0,"area":null},{"id":"2609.37784","title":"Planetary Feature Fields are Scalable Earth Representations","created":"2026-09-29","cited_by_count":0,"area":null}],"next_cursor":null}