Summary of Generative Diffusion Modeling: a Practical Handbook, by Zihan Ding et al.
Generative Diffusion Modeling: A Practical Handbookby Zihan Ding, Chi JinFirst submitted to arxiv on: 22…
Summary of The Potential Of Convolutional Neural Networks For Cancer Detection, by Hossein Molaeian et al.
The Potential of Convolutional Neural Networks for Cancer Detectionby Hossein Molaeian, Kaveh Karamjani, Sina Teimouri,…
Summary of Where Did Your Model Learn That? Label-free Influence For Self-supervised Learning, by Nidhin Harilal et al.
Where Did Your Model Learn That? Label-free Influence for Self-supervised Learningby Nidhin Harilal, Amit Kiran…
Summary of Enhancing Item Tokenization For Generative Recommendation Through Self-improvement, by Runjin Chen et al.
Enhancing Item Tokenization for Generative Recommendation through Self-Improvementby Runjin Chen, Mingxuan Ju, Ngoc Bui, Dimosthenis…
Summary of Wpmixer: Efficient Multi-resolution Mixing For Long-term Time Series Forecasting, by Md Mahmuddun Nabi Murad et al.
WPMixer: Efficient Multi-Resolution Mixing for Long-Term Time Series Forecastingby Md Mahmuddun Nabi Murad, Mehmet Aktukmak,…
Summary of Hierarchically Gated Experts For Efficient Online Continual Learning, by Kevin Luong and Michael Thielscher
Hierarchically Gated Experts for Efficient Online Continual Learningby Kevin Luong, Michael ThielscherFirst submitted to arxiv…
Summary of Foundation Model For Lossy Compression Of Spatiotemporal Scientific Data, by Xiao Li and Jaemoon Lee and Anand Rangarajan and Sanjay Ranka
Foundation Model for Lossy Compression of Spatiotemporal Scientific Databy Xiao Li, Jaemoon Lee, Anand Rangarajan,…
Summary of Matchminer-ai: An Open-source Solution For Cancer Clinical Trial Matching, by Ethan Cerami et al.
MatchMiner-AI: An Open-Source Solution for Cancer Clinical Trial Matchingby Ethan Cerami, Pavel Trukhanov, Morgan A.…
Summary of Brain-to-text Benchmark ’24: Lessons Learned, by Francis R. Willett et al.
Brain-to-Text Benchmark ’24: Lessons Learnedby Francis R. Willett, Jingyuan Li, Trung Le, Chaofei Fan, Mingfei…
Summary of Fedmeld: a Model-dispersal Federated Learning Framework For Space-ground Integrated Networks, by Qian Chen et al.
FedMeld: A Model-dispersal Federated Learning Framework for Space-ground Integrated Networksby Qian Chen, Xianhao Chen, Kaibin…