{"total":31,"rows":[{"id":"2312.04564","title":"EAGLES: Efficient Accelerated 3D Gaussians with Lightweight EncodingS","created":"2023-12-07","cited_by_count":196,"area":null},{"id":"2212.14593","title":"NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise Modeling","created":"2022-12-30","cited_by_count":51,"area":null},{"id":"2203.03761","title":"The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning","created":"2022-03-07","cited_by_count":39,"area":null},{"id":"2309.15848","title":"SHACIRA: Scalable HAsh-grid Compression for Implicit Neural Representations","created":"2023-09-27","cited_by_count":31,"area":null},{"id":"2402.18152","title":"Boosting Neural Representations for Videos with a Conditional Decoder","created":"2024-02-28","cited_by_count":29,"area":null},{"id":"2102.08329","title":"An Information-Theoretic Justification for Model Pruning","created":"2021-02-16","cited_by_count":25,"area":null},{"id":"2104.12456","title":"3D Scene Compression through Entropy Penalized Neural Representation Functions","created":"2021-04-26","cited_by_count":23,"area":null},{"id":"2111.08988","title":"LVAC: Learned Volumetric Attribute Compression for Point Clouds using Coordinate Based Networks","created":"2021-11-17","cited_by_count":19,"area":null},{"id":"2404.02185","title":"NeRFCodec: Neural Feature Compression Meets Neural Radiance Fields for Memory-Efficient Scene Representation","created":"2024-04-02","cited_by_count":16,"area":null},{"id":"2411.05239","title":"ZipNN: Lossless Compression for AI Models","created":"2024-11-07","cited_by_count":14,"area":null},{"id":"2309.17182","title":"RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations","created":"2023-09-29","cited_by_count":9,"area":null},{"id":"2102.07725","title":"Neural Network Compression for Noisy Storage Devices","created":"2021-02-15","cited_by_count":8,"area":null},{"id":"2311.14208","title":"ECRF: Entropy-Constrained Neural Radiance Fields Compression with Frequency Domain Optimization","created":"2023-11-23","cited_by_count":8,"area":null},{"id":"2204.02965","title":"LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification","created":"2022-04-06","cited_by_count":7,"area":null},{"id":"2404.15198","title":"Lossless and Near-Lossless Compression for Foundation Models","created":"2024-04-05","cited_by_count":5,"area":null},{"id":"2107.05298","title":"HEMP: High-order Entropy Minimization for neural network comPression","created":"2021-07-12","cited_by_count":4,"area":null},{"id":"2308.04269","title":"Lossy and Lossless (L$^2$) Post-training Model Size Compression","created":"2023-08-08","cited_by_count":4,"area":null},{"id":"2406.08943","title":"Neural NeRF Compression","created":"2024-06-13","cited_by_count":4,"area":null},{"id":"2505.20646","title":"Binarized Neural Networks Converge Toward Algorithmic Simplicity: Empirical Support for the Learning-as-Compression Hypothesis","created":"2025-05-27","cited_by_count":3,"area":null},{"id":"2210.04323","title":"Deep Learning Inference Frameworks Benchmark","created":"2022-10-09","cited_by_count":2,"area":null},{"id":"2301.07806","title":"Federated Automatic Differentiation","created":"2023-01-18","cited_by_count":2,"area":null},{"id":"2405.06038","title":"From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks","created":"2024-05-09","cited_by_count":2,"area":null},{"id":"2208.14046","title":"A Deep Neural Networks ensemble workflow from hyperparameter search to inference leveraging GPU clusters","created":"2022-08-30","cited_by_count":1,"area":null},{"id":"2303.03106","title":"Rotation Invariant Quantization for Model Compression","created":"2023-03-03","cited_by_count":1,"area":null},{"id":"2309.02855","title":"Bandwidth-efficient Inference for Neural Image Compression","created":"2023-09-06","cited_by_count":1,"area":null},{"id":"2403.17886","title":"Neural Embedding Compression For Efficient Multi-Task Earth Observation Modelling","created":"2024-03-26","cited_by_count":1,"area":null},{"id":"2305.05274","title":"DietCNN: Multiplication-free Inference for Quantized CNNs","created":"2023-05-09","cited_by_count":0,"area":null},{"id":"2312.15966","title":"Federated Hyperdimensional Computing","created":"2023-12-26","cited_by_count":0,"area":null},{"id":"2406.06237","title":"Efficient Neural Compression with Inference-time Decoding","created":"2024-06-10","cited_by_count":0,"area":null},{"id":"2501.09531","title":"MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights","created":"2025-01-16","cited_by_count":0,"area":null},{"id":"2609.31564","title":"Weight Pair Encoding: Inducing a Smaller Grammar in Neural Network Weights","created":"2026-09-25","cited_by_count":0,"area":null}],"next_cursor":null}