Christoph Studer
Artificial Intelligence · 2008–2019
A researcher in the Science corpus: 15 papers; trusts 185 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 150 citations into it; #27,887 of 35,345 by trust here, #13,353 by citations
- Safety, Robustness & Interpretability — 98 citations into it; #1,893 of 2,251 by trust here, #419 by citations
- Computer Vision and Pattern Recognition — 82 citations into it; #13,033 of 21,575 by trust here, #10,500 by citations
- Electrical and Electronic Engineering — 76 citations into it; #8,598 of 16,539 by trust here, #9,631 by citations
- Computer Networks and Communications — 54 citations into it; #6,173 of 9,886 by trust here, #5,518 by citations
- Computational Mechanics — 43 citations into it; #2,683 of 10,001 by trust here, #4,937 by citations
- Signal Processing — 32 citations into it
- Optimization & Training — 29 citations into it
Whom Christoph Studer trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- E.J. Candes
- Arogyaswami Paulraj
- Bertrand M. Hochwald
- Vinko Erceg
- Gitta Kutyniok
- Alex Krizhevsky
- Stephan ten Brink
- Antonin Chambolle
- Robert Tibshirani
- Geoffrey E. Hinton
Who trusts Christoph Studer overall
- Tom Goldstein
- Shaoshi Yang
- Emil Björnson
- Chen Zhu
- Ali Shafahi
- Soham De
- Lajos Hanzo
- Zhiyi Tian
- Zheng Xu
- W. Ronny Huang
Papers from Christoph Studer's perspective
Ordered by how strongly the researchers Christoph Studer 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
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Training Quantized Nets: A Deeper Understanding (2017) — 230 citations
- ASIC Implementation of Soft-Input Soft-Output MIMO Detection Using MMSE Parallel Interference Cancellation (2011) — 314 citations
- Throughput Analysis of Massive MIMO Uplink With Low-Resolution ADCs (2016) — 403 citations
- A Field Guide to Forward-Backward Splitting with a FASTA Implementation (2014) — 252 citations
- Soft-output sphere decoding: algorithms and VLSI implementation (2008) — 397 citations
- Quantized Precoding for Massive MU-MIMO (2016) — 328 citations
- Large-Scale MIMO Detection for 3GPP LTE: Algorithms and FPGA Implementations (2014) — 374 citations
- Matrix recovery from quantized and corrupted measurements (2014) — 34 citations
- Adversarial Training for Free! (2019) — 1,469 citations
- Transferable Clean-Label Poisoning Attacks on Deep Neural Nets (2019) — 327 citations
- Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks (2018) — 1,286 citations
- Are adversarial examples inevitable? (2018) — 305 citations
- PhaseMax: Convex Phase Retrieval via Basis Pursuit (2016) — 291 citations
- Signal representations with minimum ℓ∞-norm (2012) — 37 citations
- MIMO transmission with residual transmit-RF impairments (2010) — 306 citations