Steiner Tree Balancing in Distributed Algorithm for Multicast Connection Setup. - Roman Novak; Joze Rugelj (Applied Informatics, 1994)

Adaptive Steiner tree balancing in distributed algorithm for multicast connection setup. - Roman Novak; Gorazd Kandus (Microprocess. Microprogramming, 1994)

Distributed Rerouting of Multicast Connections with Delay Constraints. - Roman Novak; Joze Rugelj (Euro-PDS, 1997)

Rerouting of Multicast Connections with Quality-of-Service Constraints. - Roman Novak; Joze Rugelj (EUROMICRO, 1997)

Automatic Test Case Generation from the Industrial Point of View: Conformance Testing in IskraTEL. - Marjeta Frey-Pucko; Monika Kapus-Kolar; Roman Novak (IWTCS, 1999)

SEPAM – CMM Implementation for Developing Telecommunications Systems. - Marjeta Frey-Pucko; Roman Novak; Gorazd Kandus (EUROMICRO, 2001)

A note on distributed multicast routing in point-to-point networks. - Roman Novak; Joze Rugelj; Gorazd Kandus (Comput. Oper. Res., 2001)

Slovene smart card and IP based health-care information system infrastructure. - Denis Trcek; Roman Novak; Gorazd Kandus; Marjan Suselj (Int. J. Medical Informatics, 2001)

SPA-Based Adaptive Chosen-Ciphertext Attack on RSA Implementation. - Roman Novak (Public Key Cryptography, 2002)

Side-Channel Attack on Substitution Blocks. - Roman Novak (ACNS, 2003)

Sign-Based Differential Power Analysis. - Roman Novak (WISA, 2003)

Home Agent Placement Optimization for HAP-Based Network Mobility. - Andrej Vilhar; Roman Novak (ISWCS, 2005)

Proxy MAP for Intra-domain Route Optimization in Hierarchical Mobile IP. - Roman Novak (IEICE Trans. Commun., 2006)

Policy relationship annotations of predefined AS-level topologies. - Andrej Vilhar; Roman Novak (Comput. Networks, 2008)

The impact of network topology on the performance of MAP selection algorithms. - Andrej Vilhar; Roman Novak; Gorazd Kandus (Comput. Networks, 2010)

Loop Optimization for Divergence Reduction on GPUs with SIMT Architecture. - Roman Novak (IEEE Trans. Parallel Distributed Syst., 2015)

Exploring the Neural Algorithm of Artistic Style. - Yaroslav Nikulin; Roman Novak (CoRR, 2016)

Iterative Refinement for Machine Translation. - Roman Novak; Michael Auli; David Grangier (CoRR, 2016)

Improving the Neural Algorithm of Artistic Style. - Roman Novak; Yaroslav Nikulin (CoRR, 2016)

Combining Measurements and Simulations for Evaluation of Tracking Algorithms. - Klemen Bregar; Roman Novak; Mihael Mohorcic (EuCNC, 2018)

Deep Neural Networks as Gaussian Processes. - Jaehoon Lee 001; Yasaman Bahri; Roman Novak; Samuel S. Schoenholz; Jeffrey Pennington; Jascha Sohl-Dickstein (ICLR (Poster), 2018)

Sensitivity and Generalization in Neural Networks: an Empirical Study. - Roman Novak; Yasaman Bahri; Daniel A. Abolafia; Jeffrey Pennington; Jascha Sohl-Dickstein (ICLR (Poster), 2018)

Bayesian Convolutional Neural Networks with Many Channels are Gaussian Processes. - Roman Novak; Lechao Xiao; Jaehoon Lee 001; Yasaman Bahri; Daniel A. Abolafia; Jeffrey Pennington; Jascha Sohl-Dickstein (CoRR, 2018)

Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes. - Roman Novak; Lechao Xiao; Yasaman Bahri; Jaehoon Lee 001; Greg Yang; Jiri Hron; Daniel A. Abolafia; Jeffrey Pennington; Jascha Sohl-Dickstein (ICLR (Poster), 2019)

Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent. - Jaehoon Lee 001; Lechao Xiao; Samuel S. Schoenholz; Yasaman Bahri; Roman Novak; Jascha Sohl-Dickstein; Jeffrey Pennington (NeurIPS, 2019)

Evaluation of range-based indoor tracking algorithms by merging simulation and measurements. - Klemen Bregar; Roman Novak; Mihael Mohorcic (EURASIP J. Wirel. Commun. Netw., 2019)

Neural Tangents: Fast and Easy Infinite Neural Networks in Python. - Roman Novak; Lechao Xiao; Jiri Hron; Jaehoon Lee 001; Alexander A. Alemi; Jascha Sohl-Dickstein; Samuel S. Schoenholz (ICLR, 2020)

Infinite attention: NNGP and NTK for deep attention networks. - Jiri Hron; Yasaman Bahri; Jascha Sohl-Dickstein; Roman Novak (ICML, 2020)

Finite Versus Infinite Neural Networks: an Empirical Study. - Jaehoon Lee 001; Samuel S. Schoenholz; Jeffrey Pennington; Ben Adlam; Lechao Xiao; Roman Novak; Jascha Sohl-Dickstein (NeurIPS, 2020)

On the infinite width limit of neural networks with a standard parameterization. - Jascha Sohl-Dickstein; Roman Novak; Samuel S. Schoenholz; Jaehoon Lee 001 (CoRR, 2020)

Exact posterior distributions of wide Bayesian neural networks. - Jiri Hron; Yasaman Bahri; Roman Novak; Jeffrey Pennington; Jascha Sohl-Dickstein (CoRR, 2020)

Dataset Distillation with Infinitely Wide Convolutional Networks. - Timothy Nguyen; Roman Novak; Lechao Xiao; Jaehoon Lee 001 (NeurIPS, 2021)

Three-Point Synchrophasor Estimator With Better Off-Nominal Frequency Leakage Reduction. - Roman Novak (IEEE Access, 2021)

Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling. - Jiri Hron; Roman Novak; Jeffrey Pennington; Jascha Sohl-Dickstein (ICML, 2022)

Fast Finite Width Neural Tangent Kernel. - Roman Novak; Jascha Sohl-Dickstein; Samuel S. Schoenholz (ICML, 2022)

Fast Neural Kernel Embeddings for General Activations. - Insu Han; Amir Zandieh; Jaehoon Lee 001; Roman Novak; Lechao Xiao; Amin Karbasi (NeurIPS, 2022)

Inconsistent Rays in Propagation Prediction by Ray Launching in Rectangular Tunnels. - Roman Novak (IEEE Access, 2022)

Quantum Algorithms in Electromagnetic Propagation Modelling for Telecommunications. - Roman Novak (IEEE Access, 2023)

Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5? - 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; et al. (CoRR, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Small-scale proxies for large-scale Transformer training instabilities. - Mitchell Wortsman; Peter J. Liu; Lechao Xiao; Katie E. Everett; Alexander A. Alemi; Ben Adlam; John D. Co-Reyes; Izzeddin Gur; Abhishek Kumar; Roman Novak; Jeffrey Pennington; Jascha Sohl-Dickstein; et al. (ICLR, 2024)

Scaling Exponents Across Parameterizations and Optimizers. - Katie E. Everett; Lechao Xiao; Mitchell Wortsman; Alexander A. Alemi; Roman Novak; Peter J. Liu; Izzeddin Gur; Jascha Sohl-Dickstein; Leslie Pack Kaelbling; Jaehoon Lee 001; Jeffrey Pennington (ICML, 2024)

Quantum Algorithm for Solving the Wave Equation on a Hexagonal Grid. - Roman Novak (IEEE Access, 2024)

Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability. - Jiri Hron; Laura Culp; Gamaleldin F. Elsayed; Rosanne Liu; Ben Adlam; Maxwell L. Bileschi; Bernd Bohnet; JD Co-Reyes; Noah Fiedel; C. Daniel Freeman; Izzeddin Gur; Kathleen Kenealy; et al. (CoRR, 2024)

Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. - Avi Singh; John D. Co-Reyes; Rishabh Agarwal; Ankesh Anand; Piyush Patil; Xavier Garcia; Peter J. Liu; James Harrison; Jaehoon Lee 001; Kelvin Xu; Aaron T. Parisi; Abhishek Kumar; et al. (Trans. Mach. Learn. Res., 2024)