PinnedPrakash KagithainTowards Data ScienceNeurIPS 2020 Papers: Takeaways of a Deep Learning Engineer (Part 2 of 3)— Computer VisionTechniques and insights for applied deep learning (computer vision) from papers published at NeurIPS 2020Dec 5, 2020Dec 5, 2020
PinnedPrakash KagithainTowards Data ScienceNeurIPS 2020 Papers: A Deep Learning Engineer’s TakeawayTechniques and insights for applied deep learning from papers published at NeurIPS 2020.Nov 27, 2020Nov 27, 2020
Prakash KagithainHeartbeatKnowledge Distillation Research ReviewThe latest advances and insights for Neural Network model compression with Knowledge DistillationFeb 5, 2021Feb 5, 2021
Prakash KagithainHeartbeatNeural Network Quantization Research ReviewThe latest advances and insights for Neural Network model compression with QuantizationJan 19, 2021Jan 19, 2021
Prakash KagithainHeartbeatNeural Network Pruning Research Review 2020The latest advances and insights for Neural Network model compression with PruningDec 24, 20201Dec 24, 20201
Prakash KagithaICLR 2020 papers: On Compositional/Systematic generalization (including ours)An introduction to systematic generalization and a summary of 4 papers from ICLR 2020Apr 26, 2020Apr 26, 2020
Prakash KagithainAkaike TechnologiesComputer Vision and Computer Vision appliedThe beginning, the rise and the prospect of computer visionOct 24, 2019Oct 24, 2019
Prakash KagithaThis Is the Meaning of Everything, If It ExistsEverything comes down to ‘the relationship’ between the oblivion and everything; and it is the answer for everything, if it’s not trivialDec 15, 20181Dec 15, 20181
Prakash KagithainTowards Data ScienceNIPS/NeurIPS 2018: Best* of the First Two Poster SessionsA reading list from 330+ papers, grouped based on their utility or virtueDec 4, 20181Dec 4, 20181
Prakash KagithainTowards Data ScienceReading Abstracts from NIPS/NeurIPS 2018! Here is What I LearnedNeurIPS 2018 EXPO just began!! Lets start the funDec 2, 20181Dec 2, 20181
