Mufti Mahmud
Artificial Intelligence · 2009–2024
A researcher in the Science corpus: 6 papers; trusts 204 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 178 citations into it
- Computer Vision and Pattern Recognition — 94 citations into it
- Molecular Biology — 50 citations into it
- Safety, Robustness & Interpretability — 50 citations into it
- Model Architectures — 34 citations into it
- Cognitive Neuroscience — 30 citations into it
- Reinforcement Learning — 21 citations into it
- Signal Processing — 21 citations into it
Whom Mufti Mahmud trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Alex Krizhevsky
- Yann LeCun
- Richard S. Sutton
- Ruslan Salakhutdinov
- Ilya Sutskever
- Karen Simonyan
- J. Urgen Schmidhuber
Who trusts Mufti Mahmud overall
Papers from Mufti Mahmud's perspective
Ordered by how strongly the researchers Mufti Mahmud trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Going deeper with convolutions
Their papers
- Deep Learning in Mining Biological Data (2020) — 333 citations
- Applications of Deep Learning and Reinforcement Learning to Biological Data (2017) — 707 citations
- Interpreting artificial intelligence models: a systematic review on the application of LIME and SHAP in Alzheimer’s disease detection (2024) — 343 citations
- Interpreting Black-Box Models: A Review on Explainable Artificial Intelligence (2023) — 1,661 citations
- 2022 roadmap on neuromorphic computing and engineering (2021) — 589 citations
- Knowledge-based Systems (2009) — 1,262 citations