M. Milosavljević

Statistical and Nonlinear Physics · 2019

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Statistical and Nonlinear Physics — 12 citations into it
• Artificial Intelligence — 8 citations into it
• Computational Mechanics — 8 citations into it
• AI for Physical Sciences — 5 citations into it

Whom M. Milosavljević trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Xiaolin Li
2. Diederik P. Kingma
3. Xavier Glorot
4. Justin A. Sirignano
5. Alexander I. J. Forrester
6. Ivo Babuska
7. Benjamin Peherstorfer
8. Yoshua Bengio
9. Maizar Raissi
10. Jimmy Ba

Papers from M. Milosavljević's perspective

Ordered by how strongly the researchers M. Milosavljević trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Understanding the difficulty of training deep feedforward neural networks
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Learning Multiple Layers of Features from Tiny Images
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Solving Irregular and Data-enriched Differential Equations using Deep Neural Networks (2019) — 23 citations