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Roman Novak
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2020 – today
- 2023
- [j11]Roman Novak:
Quantum Algorithms in Electromagnetic Propagation Modelling for Telecommunications. IEEE Access 11: 111545-111565 (2023) - [i18]Mitchell Wortsman, Peter J. Liu, Lechao Xiao, Katie Everett, Alex Alemi, Ben Adlam, John D. Co-Reyes, Izzeddin Gur, Abhishek Kumar, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein, Kelvin Xu, Jaehoon Lee, Justin Gilmer, Simon Kornblith:
Small-scale proxies for large-scale Transformer training instabilities. CoRR abs/2309.14322 (2023) - [i17]C. Daniel Freeman, Laura Culp, Aaron Parisi, Maxwell L. Bileschi, Gamaleldin F. Elsayed, Alex Rizkowsky, Isabelle Simpson, Alex Alemi, Azade Nova, Ben Adlam, Bernd Bohnet, Gaurav Mishra, Hanie Sedghi, Igor Mordatch, Izzeddin Gur, Jaehoon Lee, John D. Co-Reyes, Jeffrey Pennington, Kelvin Xu, Kevin Swersky, Kshiteej Mahajan, Lechao Xiao, Rosanne Liu, Simon Kornblith, Noah Constant, Peter J. Liu, Roman Novak, Yundi Qian, Noah Fiedel, Jascha Sohl-Dickstein:
Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5? CoRR abs/2311.07587 (2023) - [i16]Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron Parisi, Abhishek Kumar, Alex Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin F. Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel:
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. CoRR abs/2312.06585 (2023) - 2022
- [j10]Roman Novak:
Inconsistent Rays in Propagation Prediction by Ray Launching in Rectangular Tunnels. IEEE Access 10: 122548-122559 (2022) - [c21]Jiri Hron, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein:
Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling. ICML 2022: 8926-8945 - [c20]Roman Novak, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
Fast Finite Width Neural Tangent Kernel. ICML 2022: 17018-17044 - [c19]Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi:
Fast Neural Kernel Embeddings for General Activations. NeurIPS 2022 - [i15]Jiri Hron, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein:
Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling. CoRR abs/2206.07673 (2022) - [i14]Roman Novak, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
Fast Finite Width Neural Tangent Kernel. CoRR abs/2206.08720 (2022) - [i13]Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi:
Fast Neural Kernel Embeddings for General Activations. CoRR abs/2209.04121 (2022) - 2021
- [j9]Roman Novak:
Three-Point Synchrophasor Estimator With Better Off-Nominal Frequency Leakage Reduction. IEEE Access 9: 50126-50137 (2021) - [c18]Timothy Nguyen, Roman Novak, Lechao Xiao, Jaehoon Lee:
Dataset Distillation with Infinitely Wide Convolutional Networks. NeurIPS 2021: 5186-5198 - [i12]Timothy Nguyen, Roman Novak, Lechao Xiao, Jaehoon Lee:
Dataset Distillation with Infinitely Wide Convolutional Networks. CoRR abs/2107.13034 (2021) - 2020
- [c17]Roman Novak, Lechao Xiao, Jiri Hron, Jaehoon Lee, Alexander A. Alemi, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
Neural Tangents: Fast and Easy Infinite Neural Networks in Python. ICLR 2020 - [c16]Jiri Hron, Yasaman Bahri, Jascha Sohl-Dickstein, Roman Novak:
Infinite attention: NNGP and NTK for deep attention networks. ICML 2020: 4376-4386 - [c15]Jaehoon Lee, Samuel S. Schoenholz, Jeffrey Pennington, Ben Adlam, Lechao Xiao, Roman Novak, Jascha Sohl-Dickstein:
Finite Versus Infinite Neural Networks: an Empirical Study. NeurIPS 2020 - [i11]Jascha Sohl-Dickstein, Roman Novak, Samuel S. Schoenholz, Jaehoon Lee:
On the infinite width limit of neural networks with a standard parameterization. CoRR abs/2001.07301 (2020) - [i10]Jiri Hron, Yasaman Bahri, Jascha Sohl-Dickstein, Roman Novak:
Infinite attention: NNGP and NTK for deep attention networks. CoRR abs/2006.10540 (2020) - [i9]Jiri Hron, Yasaman Bahri, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein:
Exact posterior distributions of wide Bayesian neural networks. CoRR abs/2006.10541 (2020) - [i8]Jaehoon Lee, Samuel S. Schoenholz, Jeffrey Pennington, Ben Adlam, Lechao Xiao, Roman Novak, Jascha Sohl-Dickstein:
Finite Versus Infinite Neural Networks: an Empirical Study. CoRR abs/2007.15801 (2020)
2010 – 2019
- 2019
- [j8]Klemen Bregar, Roman Novak, Mihael Mohorcic:
Evaluation of range-based indoor tracking algorithms by merging simulation and measurements. EURASIP J. Wirel. Commun. Netw. 2019: 173 (2019) - [c14]Roman Novak, Lechao Xiao, Yasaman Bahri, Jaehoon Lee, Greg Yang, Jiri Hron, Daniel A. Abolafia, Jeffrey Pennington, Jascha Sohl-Dickstein:
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes. ICLR (Poster) 2019 - [c13]Jaehoon Lee, Lechao Xiao, Samuel S. Schoenholz, Yasaman Bahri, Roman Novak, Jascha Sohl-Dickstein, Jeffrey Pennington:
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent. NeurIPS 2019: 8570-8581 - [i7]Roman Novak, Lechao Xiao, Jiri Hron, Jaehoon Lee, Alexander A. Alemi, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
Neural Tangents: Fast and Easy Infinite Neural Networks in Python. CoRR abs/1912.02803 (2019) - 2018
- [c12]Klemen Bregar, Roman Novak, Mihael Mohorcic:
Combining Measurements and Simulations for Evaluation of Tracking Algorithms. EuCNC 2018: 1-250 - [c11]Jaehoon Lee, Yasaman Bahri, Roman Novak, Samuel S. Schoenholz, Jeffrey Pennington, Jascha Sohl-Dickstein:
Deep Neural Networks as Gaussian Processes. ICLR (Poster) 2018 - [c10]Roman Novak, Yasaman Bahri, Daniel A. Abolafia, Jeffrey Pennington, Jascha Sohl-Dickstein:
Sensitivity and Generalization in Neural Networks: an Empirical Study. ICLR (Poster) 2018 - [i6]Roman Novak, Yasaman Bahri, Daniel A. Abolafia, Jeffrey Pennington, Jascha Sohl-Dickstein:
Sensitivity and Generalization in Neural Networks: an Empirical Study. CoRR abs/1802.08760 (2018) - [i5]Roman Novak, Lechao Xiao, Jaehoon Lee, Yasaman Bahri, Daniel A. Abolafia, Jeffrey Pennington, Jascha Sohl-Dickstein:
Bayesian Convolutional Neural Networks with Many Channels are Gaussian Processes. CoRR abs/1810.05148 (2018) - 2017
- [i4]Jaehoon Lee, Yasaman Bahri, Roman Novak, Samuel S. Schoenholz, Jeffrey Pennington, Jascha Sohl-Dickstein:
Deep Neural Networks as Gaussian Processes. CoRR abs/1711.00165 (2017) - 2016
- [i3]Yaroslav Nikulin, Roman Novak:
Exploring the Neural Algorithm of Artistic Style. CoRR abs/1602.07188 (2016) - [i2]Roman Novak, Yaroslav Nikulin:
Improving the Neural Algorithm of Artistic Style. CoRR abs/1605.04603 (2016) - [i1]Roman Novak, Michael Auli, David Grangier:
Iterative Refinement for Machine Translation. CoRR abs/1610.06602 (2016) - 2015
- [j7]Roman Novak:
Loop Optimization for Divergence Reduction on GPUs with SIMT Architecture. IEEE Trans. Parallel Distributed Syst. 26(6): 1633-1642 (2015) - 2010
- [j6]Andrej Vilhar, Roman Novak, Gorazd Kandus:
The impact of network topology on the performance of MAP selection algorithms. Comput. Networks 54(7): 1197-1209 (2010)
2000 – 2009
- 2008
- [j5]Andrej Vilhar, Roman Novak:
Policy relationship annotations of predefined AS-level topologies. Comput. Networks 52(15): 2859-2871 (2008) - 2006
- [j4]Roman Novak:
Proxy MAP for Intra-domain Route Optimization in Hierarchical Mobile IP. IEICE Trans. Commun. 89-B(2): 472-481 (2006) - 2005
- [c9]Andrej Vilhar, Roman Novak:
Home Agent Placement Optimization for HAP-Based Network Mobility. ISWCS 2005: 873-877 - 2003
- [c8]Roman Novak:
Side-Channel Attack on Substitution Blocks. ACNS 2003: 307-318 - [c7]Roman Novak:
Sign-Based Differential Power Analysis. WISA 2003: 203-216 - 2002
- [c6]Roman Novak:
SPA-Based Adaptive Chosen-Ciphertext Attack on RSA Implementation. Public Key Cryptography 2002: 252-262 - 2001
- [j3]Roman Novak, Joze Rugelj, Gorazd Kandus:
A note on distributed multicast routing in point-to-point networks. Comput. Oper. Res. 28(12): 1149-1164 (2001) - [j2]Denis Trcek, Roman Novak, Gorazd Kandus, Marjan Suselj:
Slovene smart card and IP based health-care information system infrastructure. Int. J. Medical Informatics 61(1): 33-43 (2001) - [c5]Marjeta Frey-Pucko, Roman Novak, Gorazd Kandus:
SEPAM -- CMM Implementation for Developing Telecommunications Systems. EUROMICRO 2001: 272-278
1990 – 1999
- 1999
- [c4]Marjeta Frey-Pucko, Monika Kapus-Kolar, Roman Novak:
Automatic Test Case Generation from the Industrial Point of View: Conformance Testing in IskraTEL. IWTCS 1999: 347-362 - 1997
- [c3]Roman Novak, Joze Rugelj:
Distributed Rerouting of Multicast Connections with Delay Constraints. Euro-PDS 1997: 237-242 - [c2]Roman Novak, Joze Rugelj:
Rerouting of Multicast Connections with Quality-of-Service Constraints. EUROMICRO 1997: 301-307 - 1994
- [j1]Roman Novak, Gorazd Kandus:
Adaptive Steiner tree balancing in distributed algorithm for multicast connection setup. Microprocess. Microprogramming 40(10-12): 795-798 (1994) - [c1]Roman Novak, Joze Rugelj:
Steiner Tree Balancing in Distributed Algorithm for Multicast Connection Setup. Applied Informatics 1994: 43-46
Coauthor Index
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