On the Number of 3-Edge Colorings of Cubic Graphs. - Christian Szegedy (Eur. J. Comb., 2002)

Symplectic Spaces And Ear-Decomposition Of Matroids. - Balázs Szegedy; Christian Szegedy (Comb., 2006)

Delay optimization of linear depth boolean circuits with prescribed input arrival times. - Dieter Rautenbach; Christian Szegedy; Jürgen Werber (J. Discrete Algorithms, 2006)

Timing optimization by restructuring long combinatorial paths. - Jürgen Werber; Dieter Rautenbach; Christian Szegedy (ICCAD, 2007)

A morphing approach to address placement stability. - Philip Chong; Christian Szegedy (ISPD, 2007)

The delay of circuits whose inputs have specified arrival times. - Dieter Rautenbach; Christian Szegedy; Jürgen Werber (Discret. Appl. Math., 2007)

A class of problems for which cyclic relaxation converges linearly. - Dieter Rautenbach; Christian Szegedy (Comput. Optim. Appl., 2008)

On the cost of optimal alphabetic code trees with unequal letter costs. - Dieter Rautenbach; Christian Szegedy; Jürgen Werber (Eur. J. Comb., 2008)

Modular code generation from synchronous block diagrams: modularity vs. code size. - Roberto Lublinerman; Christian Szegedy; Stavros Tripakis (POPL, 2009)

Deep Neural Networks for Object Detection. - Christian Szegedy; Alexander Toshev; Dumitru Erhan (NIPS, 2013)

Scalable Object Detection Using Deep Neural Networks. - Dumitru Erhan; Christian Szegedy; Alexander Toshev; Dragomir Anguelov (CVPR, 2014)

DeepPose: Human Pose Estimation via Deep Neural Networks. - Alexander Toshev; Christian Szegedy (CVPR, 2014)

Scalable, High-Quality Object Detection. - Christian Szegedy; Scott E. Reed; Dumitru Erhan; Dragomir Anguelov (CoRR, 2014)

Intriguing properties of neural networks. - Christian Szegedy; Wojciech Zaremba; Ilya Sutskever; Joan Bruna; Dumitru Erhan; Ian J. Goodfellow; Rob Fergus (ICLR (Poster), 2014)

Going deeper with convolutions. - Christian Szegedy; Wei Liu 015; Yangqing Jia; Pierre Sermanet; Scott E. Reed; Dragomir Anguelov; Dumitru Erhan; Vincent Vanhoucke; Andrew Rabinovich (CVPR, 2015)

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. - Sergey Ioffe; Christian Szegedy (ICML, 2015)

Explaining and Harnessing Adversarial Examples. - Ian J. Goodfellow; Jonathon Shlens; Christian Szegedy (ICLR (Poster), 2015)

Training Deep Neural Networks on Noisy Labels with Bootstrapping. - Scott E. Reed; Honglak Lee; Dragomir Anguelov; Christian Szegedy; Dumitru Erhan; Andrew Rabinovich (ICLR (Workshop), 2015)

Large Scale Business Discovery from Street Level Imagery. - Qian Yu; Christian Szegedy; Martin C. Stumpe; Liron Yatziv; Vinay D. Shet; Julian Ibarz; Sacha Arnoud (CoRR, 2015)

Rethinking the Inception Architecture for Computer Vision. - Christian Szegedy; Vincent Vanhoucke; Sergey Ioffe; Jonathon Shlens; Zbigniew Wojna (CVPR, 2016)

SSD: Single Shot MultiBox Detector. - Wei Liu 015; Dragomir Anguelov; Dumitru Erhan; Christian Szegedy; Scott E. Reed; Cheng-Yang Fu; Alexander C. Berg (ECCV (1), 2016)

DeepMath - Deep Sequence Models for Premise Selection. - Geoffrey Irving; Christian Szegedy; Alexander A. Alemi; Niklas Eén; François Chollet; Josef Urban (NIPS, 2016)

DeepMath - Deep Sequence Models for Premise Selection. - Alexander A. Alemi; François Chollet; Geoffrey Irving; Christian Szegedy; Josef Urban (CoRR, 2016)

Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning. - Christian Szegedy; Sergey Ioffe; Vincent Vanhoucke (CoRR, 2016)

Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning. - Christian Szegedy; Sergey Ioffe; Vincent Vanhoucke; Alexander A. Alemi (AAAI, 2017)

HolStep: A Machine Learning Dataset for Higher-order Logic Theorem Proving. - Cezary Kaliszyk; François Chollet; Christian Szegedy (ICLR (Poster), 2017)

Deep Network Guided Proof Search. - Sarah M. Loos; Geoffrey Irving; Christian Szegedy; Cezary Kaliszyk (LPAR, 2017)

HOList: An Environment for Machine Learning of Higher Order Logic Theorem Proving. - Kshitij Bansal; Sarah M. Loos; Markus N. Rabe; Christian Szegedy; Stewart Wilcox (ICML, 2019)

HOList: An Environment for Machine Learning of Higher-Order Theorem Proving (extended version). - Kshitij Bansal; Sarah M. Loos; Markus N. Rabe; Christian Szegedy; Stewart Wilcox (CoRR, 2019)

Learning to Reason in Large Theories without Imitation. - Kshitij Bansal; Sarah M. Loos; Markus N. Rabe; Christian Szegedy (CoRR, 2019)

Graph Representations for Higher-Order Logic and Theorem Proving. - Aditya Paliwal; Sarah M. Loos; Markus N. Rabe; Kshitij Bansal; Christian Szegedy (AAAI, 2020)

Mathematical Reasoning in Latent Space. - Dennis Lee 003; Christian Szegedy; Markus N. Rabe; Sarah M. Loos; Kshitij Bansal (ICLR, 2020)

A Promising Path Towards Autoformalization and General Artificial Intelligence. - Christian Szegedy (CICM, 2020)

Text Embeddings for Retrieval from a Large Knowledge Base. - Tolgahan Cakaloglu; Christian Szegedy; Xiaowei Xu 001 (RCIS, 2020)

Language Modeling for Formal Mathematics. - Markus N. Rabe; Dennis Lee 003; Kshitij Bansal; Christian Szegedy (CoRR, 2020)

Towards the Automatic Mathematician. - Markus N. Rabe; Christian Szegedy (CADE, 2021)

Mathematical Reasoning via Self-supervised Skip-tree Training. - Markus Norman Rabe; Dennis Lee 003; Kshitij Bansal; Christian Szegedy (ICLR, 2021)

LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning. - Yuhuai Wu; Markus N. Rabe; Wenda Li; Jimmy Ba; Roger B. Grosse; Christian Szegedy (ICML, 2021)

Memorizing Transformers. - Yuhuai Wu; Markus Norman Rabe; DeLesley Hutchins; Christian Szegedy (ICLR, 2022)

Hierarchical Transformers Are More Efficient Language Models. - Piotr Nawrot; Szymon Tworkowski; Michal Tyrolski; Lukasz Kaiser; Yuhuai Wu; Christian Szegedy; Henryk Michalewski (NAACL-HLT (Findings), 2022)

Autoformalization with Large Language Models. - Yuhuai Wu; Albert Qiaochu Jiang; Wenda Li; Markus N. Rabe; Charles Staats; Mateja Jamnik; Christian Szegedy (NeurIPS, 2022)

Magnushammer: A Transformer-based Approach to Premise Selection. - Maciej Mikula; Szymon Antoniak; Szymon Tworkowski; Albert Qiaochu Jiang; Jin Peng Zhou; Christian Szegedy; Lukasz Kucinski; Piotr Milos; Yuhuai Wu (CoRR, 2023)

Magnushammer: A Transformer-Based Approach to Premise Selection. - Maciej Mikula; Szymon Tworkowski; Szymon Antoniak; Bartosz Piotrowski; Albert Q. Jiang; Jin Peng Zhou; Christian Szegedy; Lukasz Kucinski; Piotr Milos; Yuhuai Wu (ICLR, 2024)

Don't Trust: Verify - Grounding LLM Quantitative Reasoning with Autoformalization. - Jin Peng Zhou; Charles Staats; Wenda Li; Christian Szegedy; Kilian Q. Weinberger; Yuhuai Wu (ICLR, 2024)

Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems. - David Dalrymple; Joar Skalse; Yoshua Bengio; Stuart Russell 001; Max Tegmark; Sanjit Seshia; Steve Omohundro; Christian Szegedy; Ben Goldhaber; Nora Ammann; Alessandro Abate; Joe Halpern; et al. (CoRR, 2024)