38 skills found · Page 1 of 2
pathak22 / Noreward Rl[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning
ttrouill / ComplexSource code for experiments in the papers "Complex Embeddings for Simple Link Prediction" (ICML 2016) and "Knowledge Graph Completion via Complex Tensor Factorization" (JMLR 2017).
bayesgroup / Variational Dropout Sparsifies DnnSparse Variational Dropout, ICML 2017
minhnhat93 / Tf SNDCGANTensorflow Implementation of the paper "Spectral Normalization for Generative Adversarial Networks" (ICML 2017 workshop)
wiseodd / Controlled Text GenerationReproducing Hu, et. al., ICML 2017's "Toward Controlled Generation of Text"
xuyxu / Deep Clustering NetworkPyTorch Implementation of "Towards K-Means-Friendly Spaces: Simultaneous Deep Learning and Clustering," Bo Yang et al., ICML'2017.
amirstar / Deep ForecastThe code of the paper 'Deep Forecast : Deep Learning-based Spatio-Temporal Forecasting", ICML Time Series Workshop 2017.
Riashat / Deep Bayesian Active LearningCode for Deep Bayesian Active Learning (ICML 2017)
lancopku / MePropmeProp: Sparsified Back Propagation for Accelerated Deep Learning (ICML 2017)
ganguli-lab / PathintCode to accompany our paper "Continual Learning Through Synaptic Intelligence" ICML 2017
uclnlp / D4Differentiable Forth Interpreter
rubenvillegas / Icml2017hierchvidTensorflow implementation of the ICML 2017 paper: Learning to Generate Long-term Future via Hierarchical Prediction
niudd / ICML 2017 Papershttps://2017.icml.cc/Conferences/2017/Schedule
dalgu90 / Splitnet WrnCode for ICML 2017 paper, SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization
takashiishida / Comp[NeurIPS 2017] [ICML 2019] Code for complementary-label learning
lunayht / DBALwithImgDataDeep Bayesian Active Learning with Image Data by Gal et al. (ICML 2017)
YingzhenLi / Dropout BBalphaImplementations of the ICML 2017 paper (with Yarin Gal)
hoonose / Robust Filter[ICML 2017] Robust estimation of mean and covariance in high dimensions
jaehong31 / CGESCombined Group and Exclusive Sparsity for Deep Neural Networks, ICML 2017
harvardnlp / Regulatory PredictionCode and Data to accompany "Dilated Convolutions for Modeling Long-Distance Genomic Dependencies", presented at the ICML 2017 Workshop on Computational Biology
