{"list":"other","total":72,"rows":[{"id":"1503.02531","title":"Distilling the Knowledge in a Neural Network","created":"2015-03-09","cited_by_count":10324},{"id":"1502.03167","title":"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift","created":"2015-02-11","cited_by_count":7005},{"id":"1801.04381","title":"MobileNetV2: Inverted Residuals and Linear Bottlenecks","created":"2018-01-13","cited_by_count":4795},{"id":"1611.07004","title":"Image-to-Image Translation with Conditional Adversarial Networks","created":"2016-11-21","cited_by_count":4527},{"id":"1604.01685","title":"The Cityscapes Dataset for Semantic Urban Scene Understanding","created":"2016-04-06","cited_by_count":4444},{"id":"1704.04861","title":"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications","created":"2017-04-17","cited_by_count":3845},{"id":"1912.04958","title":"Analyzing and Improving the Image Quality of StyleGAN","created":"2019-12-03","cited_by_count":3588},{"id":"1809.11096","title":"Large Scale GAN Training for High Fidelity Natural Image Synthesis","created":"2018-09-28","cited_by_count":2626},{"id":"1510.00149","title":"Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding","created":"2015-10-01","cited_by_count":2329},{"id":"1803.03635","title":"The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks","created":"2018-03-09","cited_by_count":2262},{"id":"1411.1784","title":"Conditional Generative Adversarial Nets","created":"2014-11-06","cited_by_count":2162},{"id":"1806.09055","title":"DARTS: Differentiable Architecture Search","created":"2018-06-24","cited_by_count":1798},{"id":"1905.00414","title":"Similarity of Neural Network Representations Revisited","created":"2019-05-01","cited_by_count":1755},{"id":"1802.05957","title":"Spectral Normalization for Generative Adversarial Networks","created":"2018-02-16","cited_by_count":1636},{"id":"2006.05525","title":"Knowledge Distillation: A Survey","created":"2020-06-09","cited_by_count":1603},{"id":"1602.07261","title":"Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning","created":"2016-02-23","cited_by_count":1512},{"id":"1611.01578","title":"Neural Architecture Search with Reinforcement Learning","created":"2016-11-05","cited_by_count":1499},{"id":"1903.07291","title":"Semantic Image Synthesis with Spatially-Adaptive Normalization","created":"2019-03-18","cited_by_count":1299},{"id":"1801.01401","title":"Demystifying MMD GANs","created":"2018-01-04","cited_by_count":1293},{"id":"1607.08022","title":"Instance Normalization: The Missing Ingredient for Fast Stylization","created":"2016-07-27","cited_by_count":1198},{"id":"1711.11585","title":"High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs","created":"2017-11-30","cited_by_count":1179},{"id":"1707.07012","title":"Learning Transferable Architectures for Scalable Image Recognition","created":"2017-07-21","cited_by_count":1101},{"id":"1807.11626","title":"MnasNet: Platform-Aware Neural Architecture Search for Mobile","created":"2018-07-31","cited_by_count":943},{"id":"1805.08318","title":"Self-Attention Generative Adversarial Networks","created":"2018-05-21","cited_by_count":809},{"id":"1908.09791","title":"Once-for-All: Train One Network and Specialize it for Efficient Deployment","created":"2019-08-26","cited_by_count":787},{"id":"1703.10593","title":"Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks","created":"2017-03-30","cited_by_count":707},{"id":"1708.06519","title":"Learning Efficient Convolutional Networks through Network Slimming","created":"2017-08-22","cited_by_count":676},{"id":"1812.00332","title":"ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware","created":"2018-12-02","cited_by_count":673},{"id":"1810.05270","title":"Rethinking the Value of Network Pruning","created":"2018-10-11","cited_by_count":599},{"id":"1812.03443","title":"FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search","created":"2018-12-09","cited_by_count":485},{"id":"1805.06085","title":"PACT: Parameterized Clipping Activation for Quantized Neural Networks","created":"2018-05-16","cited_by_count":467},{"id":"1904.00420","title":"Single Path One-Shot Neural Architecture Search with Uniform Sampling","created":"2019-03-31","cited_by_count":414},{"id":"1808.06601","title":"Video-to-Video Synthesis","created":"2018-08-20","cited_by_count":390},{"id":"1703.01041","title":"Large-Scale Evolution of Image Classifiers","created":"2017-03-03","cited_by_count":348},{"id":"1711.09485","title":"SkipNet: Learning Dynamic Routing in Convolutional Networks","created":"2017-11-26","cited_by_count":332},{"id":"1705.09914","title":"Dilated Residual Networks","created":"2017-05-28","cited_by_count":294},{"id":"1511.03643","title":"Unifying distillation and privileged information","created":"2015-11-11","cited_by_count":233},{"id":"1904.12760","title":"Progressive Differentiable Architecture Search: Bridging the Depth Gap between Search and Evaluation","created":"2019-04-29","cited_by_count":230},{"id":"1903.05134","title":"Universally Slimmable Networks and Improved Training Techniques","created":"2019-03-12","cited_by_count":221},{"id":"2003.11142","title":"BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Models","created":"2020-03-24","cited_by_count":188},{"id":"1702.07811","title":"Adaptive Neural Networks for Efficient Inference","created":"2017-02-25","cited_by_count":163},{"id":"2001.00138","title":"PatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning","created":"2020-01-01","cited_by_count":76},{"id":"2007.10396","title":"NSGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture Search","created":"2020-07-20","cited_by_count":76},{"id":"1912.09666","title":"AdaBits: Neural Network Quantization with Adaptive Bit-Widths","created":"2019-12-20","cited_by_count":64},{"id":"2005.05859","title":"Neural Architecture Transfer","created":"2020-05-12","cited_by_count":60},{"id":"1708.08917","title":"CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices","created":"2017-08-29","cited_by_count":55},{"id":"2007.02017","title":"FracBits: Mixed Precision Quantization via Fractional Bit-Widths","created":"2020-07-04","cited_by_count":55},{"id":"1909.05073","title":"PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices","created":"2019-09-06","cited_by_count":50},{"id":"2006.08198","title":"AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks","created":"2020-06-15","cited_by_count":50},{"id":"1907.03141","title":"AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates","created":"2019-07-06","cited_by_count":49},{"id":"2008.11062","title":"GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework","created":"2020-08-25","cited_by_count":44},{"id":"1912.09640","title":"AtomNAS: Fine-Grained End-to-End Neural Architecture Search","created":"2019-12-20","cited_by_count":40},{"id":"2003.03519","title":"Distilling portable Generative Adversarial Networks for Image Translation","created":"2020-03-07","cited_by_count":37},{"id":"1907.02124","title":"Non-Structured DNN Weight Pruning -- Is It Beneficial in Any Platform?","created":"2019-07-03","cited_by_count":32},{"id":"1907.10804","title":"Co-Evolutionary Compression for Unpaired Image Translation","created":"2019-07-25","cited_by_count":32},{"id":"1902.00159","title":"Compressing GANs using Knowledge Distillation","created":"2019-02-01","cited_by_count":31},{"id":"2004.01961","title":"Neural Architecture Search for Lightweight Non-Local Networks","created":"2020-04-04","cited_by_count":23},{"id":"2001.07710","title":"An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices","created":"2020-01-20","cited_by_count":18},{"id":"2004.03142","title":"Human Motion Transfer from Poses in the Wild","created":"2020-04-07","cited_by_count":17},{"id":"1912.10207","title":"Towards Efficient Training for Neural Network Quantization","created":"2019-12-21","cited_by_count":16},{"id":"1905.00136","title":"ResNet Can Be Pruned 60x: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning","created":"2019-04-30","cited_by_count":13},{"id":"1909.13396","title":"REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs","created":"2019-09-29","cited_by_count":13},{"id":"1908.11691","title":"An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM","created":"2019-08-29","cited_by_count":12},{"id":"2004.13297","title":"Neural Hair Rendering","created":"2020-04-28","cited_by_count":8},{"id":"2003.06700","title":"CoCoPIE: Making Mobile AI Sweet As PIE --Compression-Compilation Co-Design Goes a Long Way","created":"2020-03-14","cited_by_count":7},{"id":"1905.00571","title":"26ms Inference Time for ResNet-50: Towards Real-Time Execution of all DNNs on Smartphone","created":"2019-05-02","cited_by_count":6},{"id":"2004.02867","title":"Rethinking Spatially-Adaptive Normalization","created":"2020-04-06","cited_by_count":6},{"id":"2005.05758","title":"CSB-RNN: A Faster-than-Realtime RNN Acceleration Framework with Compressed Structured Blocks","created":"2020-05-11","cited_by_count":4},{"id":"1804.11239","title":"Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs","created":"2018-03-28","cited_by_count":3},{"id":"1806.01940","title":"EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching from Scratch","created":"2018-06-05","cited_by_count":2},{"id":"1905.00789","title":"Toward Extremely Low Bit and Lossless Accuracy in DNNs with Progressive ADMM","created":"2019-05-02","cited_by_count":2},{"id":"2003.12798","title":"CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks","created":"2020-03-28","cited_by_count":2}],"next_cursor":null}