N. Weinberger and R. Zamir,  "Exploration-Exploitation Tradeoff in Universal Lossy Compression," In progress.

N. Weinberger and R. Tamir, "Entropy Estimation with Samples and Queries," In progress. 

R. Tamir and N. Weinberger, "Achievable Rates of Frequency-based Channels of Unlimited Input Resolution," In progress. 

A. Kadry, Y. Zhang, and N. Weinberger, "Mean Estimation in High-Dimensional Binary Time-Inhomogeneous Markov Gaussian Mixture," In progress. 

N. Luria and N. Weinberger, "Optimal Overlap Detection of Shotgun Reads," Submitted.

V. A. Rameshwar and N. Weinberger, "On Achievable Rates Over Noisy Nanopore Channels," In progress.

Y. Gerzon, I. Shomorony, and N. Weinberger, "Capacity of Frequency-based Channels: Encoding Information in Molecular Concentrations," Submitted. Presented at ISIT 2024.

M. Dikshtein, N. Weinberger, and S. Shamai (Shitz), “The Compound Information Bottleneck Outlook,” Submitted. Presented at ISIT 2022.

N. Merhav and N. Weinberger, "A Toolbox for Refined Information-Theoretic Analyses with Applications," Foundations and Trends in Communications and Information Theory, January 2025.

I. Shufaro, N. Merlis, N. Weinberger, and S. Mannor, "On Bits and Bandits: Quantifying the Regret-Information Trade-off, " ICLR 2025, April 2025. 

V. A. Rameshwar and N. Weinberger, "Information Rates Over Multi-View Channels," Accepted to IEEE Trans. Inform. Theory, December 2024. Presented at ISIT 2024.

M. Egger, R. Bitar, A. Wachter-Zeh, D. Gündüz, and N. Weinberger, “Maximal-Capacity Discrete Memoryless Channel Identification,” IEEE Trans. Inform. Theory, vol. 71, no. 2, 1248–1265, February 2025. Presented at ISIT 2023.

O. Cohen, R. Meir, and N. Weinberger, "Statistical curriculum learning: An elimination algorithm achieving an oracle risk," COLT 2024, June 2024.

Y. Nogin, D. Sapir, T. Detinis Zur, N. Weinberger, Y. Belinkov, Y. Ebenstein, and Y. Shechtman, “OM2Seq: Learning retrieval embeddings for optical genome mapping,” Bioinformatics Advances. 

N. Weinberger and I. Shomorony, "Fundamental Limits of Reference-Based Sequence Reordering," IEEE Trans. Inform. Theory, vol. 70, no. 7, 4634–4654, July 2024. Presented at ISIT 2023.

D. Goldfarb, I. Evron, N. Weinberger, D. Soudry, and P. Hand, “The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting – An Analytical Model,” ICLR 2024, May 2024. 

N. Uzan and N. Weinberger, "A Representation-Learning Game for Classes of Prediction Tasks", ICLR 2024, May 2024. Presented at IZS 2024.

C. Zeno, G. Ongie, Y. Blumenfeld, N. Weinberger, and D. Soudry, "How do Minimum-Norm Shallow Denoisers Look in Function Space?", NeurIPS 2023, December 2023.

Y. Nogin, D. Bar-Lev, D. Hanania, T. Detinis Zur, Y. Ebenstein, E. Yaakobi, N. Weinberger, and Y. Shechtman, "Design of Optimal Labeling Patterns for Optical Genome Mapping via Information Theory" Bioinformatics, Vol. 39, Issue 10, October 2023. 

N. Weinberger and M. Yemini, "Multi-Armed Bandits with Self-Information Rewards", IEEE Trans. Inform. Theory, vol. 69, no. 11, 7160–7184, November 2023.

B. Kenig and N. Weinberger, “Quantifying the Loss of Acyclic Join Dependencies”, PODS 2023, June 2023.

A. Tsvieli and N. Weinberger, “Learning Maximum Margin Channel Decoders,” IEEE Trans. Inform. Theory, vol. 69, no. 6, 3597–3626, June 2023.  Presented at IZS 2022 and ISIT 2022.

T. Norman, N. Weinberger, and K. Y. Levy, “Robust Linear Regression for General Feature Distribution”, AISTAS 2023, April 2023.

Y. Zhang and N. Weinberger, Mean Estimation in High-Dimensional Binary Markov Gaussian Mixture Models, NeurIPS 2022, November-December 2022. See a correction note (Thanks V. Karagulyan and M. Ndaoud)

N. Weinberger, “Error Probability Bounds for Coded-Index DNA Storage Systems,”  IEEE Trans. Inform. Theory, vol. 68, no. 11, pp. 7005 - 7022, November 2022. Presented at IZS 2022.

N. Weinberger and N. Merhav, “The DNA Storage Channel: Capacity and Error Probability Bounds,”  IEEE Trans. Inform. Theory, vol. 68, no. 9, pp. 5657 - 5700, September 2022. Presented at ISIT 2022.

N. Weinberger and G. Bresler, “The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures,” Journal of Machine Learning Research, vol. 23, no. 103, pp. 1 - 79, May 2022. Presented at ITA 2020.

N. Weinberger, “Generalization Bounds and Algorithms for Learning to Communicate over Additive Noise Channels,” IEEE Trans. Inform. Theory, vol. 68, no. 3, pp. 1886 - 1921, March 2022. Presented at ISIT 2020. Code

N. Weinberger and M. Feder, “The k-vectors Algorithm: An Alternating Minimization Algorithm for Learning Regression Functions”, IEEE Trans. Inform. Theory, vol. 66, no. 11, pp. 7196 - 7221, November 2020. Presented at Allerton 2019 and IDSI 2022.

R. Tamir (Averbuch), N. Merhav, N. Weinberger, and A. G. i Fàbregas, “Large Deviations Behavior of the Logarithmic Error Probability of Random Codes,” IEEE Trans. Inform. Theory, vol. 66, no. 11, pp. 6635 - 6659, November 2020.

N. Weinberger and O. Shayevitz, “Guessing with a Bit of Help,” Entropy, vol. 22, no. 1, January 2020. Presented at ISIT 2018.

N. Weinberger and Y. Kochman, “On the Reliability Function of Distributed Hypothesis Testing Under Optimal Detection,” IEEE Trans. Inform. Theory, vol. 65, no. 8, pp. 4940 - 4965, August 2019. Presented at ITA 2017 and ISIT 2018.

R. Averbuch, N. Weinberger, and N. Merhav, “Expurgated Bounds for the Asymmetric Broadcast Channel,” IEEE Trans. Inform. Theory, vol. 65, no. 2, pp. 3412 - 3435, June 2019. Presented at IZS 2018.

N. Weinberger and O. Shayevitz, “Self-Predicting Boolean Functions,” SIAM Journal on Discrete Mathematics, vol. 33, no. 2, pp. 665-693, 2019. Presented at ITA 2018 and ISIT 2018.

S. Hu, N. Weinberger, and O. Shayevitz, “On the VC-Dimension of Binary Codes,” SIAM Journal on Discrete Mathematics, vol.32, no. 3, pp. 2161-2171, 2018. Presented at ITA 2017 and ISIT 2017.

N. Weinberger and O. Shayevitz, “On the Optimal Boolean Function for Prediction Under Quadratic Loss,” IEEE Trans. Inform. Theory, vol. 63, no. 7, pp. 4202 - 4217, July 2017. Presented at ISIT 2016.

N. Weinberger and N. Merhav, “Lower Bounds on Parameter Modulation–Estimation Under Bandwidth Constraints,” IEEE Trans. Inform. Theory, vol. 63, no. 6, pp. 3854 - 3874, June 2017. Presented at ISIT 2017.

N. Weinberger and N. Merhav, “Channel Detection in Coded Communication,” IEEE Trans. Inform. Theory, vol. 63, no. 10, pp. 6364 - 6392, October 2017. Presented at IZS 2016.

N. Weinberger and N. Merhav, “Simplified Erasure/List Decoding,” IEEE Trans. Inform. Theory, vol. 63, no. 7, pp. 4218 - 4239, July 2017. Presented at ISIT 2015.

N. Weinberger and N. Merhav, “A Large Deviations Approach to Secure Lossy Compression,” IEEE Trans. Inform. Theory, vol. 63, no. 4, pp. 2533–2559, April 2017. Presented at ITA 2016 and ISIT 2016.

W. Huleihel, N. Weinberger, and N. Merhav, “Erasure/List Random Coding Error Exponents Are Not Universally Achievable,” IEEE Trans. Inform. Theory, vol. 62, no. 10, pp. 5403–5421, October 2016. Presented at ITW 2015.

N. Weinberger and N. Merhav, “Optimum Trade-offs Between the Error Exponent and the Excess-Rate Exponent of Variable-Rate Slepian-Wolf Coding,” IEEE Trans. Inform. Theory, vol. 61, no. 4, pp. 2165–2190, April 2015. Presented at ISIT 2014 and ISIT 2015.

N. Weinberger and N. Merhav, “Codeword or Noise? Exact Random Coding Exponents for Joint Detection and Decoding,” IEEE Trans. Inform. Theory, vol. 60, no. 9, pp. 5077–5094, September 2014. Presented at ISIT 2014.

M. Egger, R. Bitar, A. Wachter-Zeh, D. Gündüz, and N. Weinberger, “Capacity-Maximizing Input Symbol Selection for Discrete Memoryless Channels,” ISIT 2024 (extended version). 

D. Freirich, N. Weinberger, and R. Meir, “The Distortion-Perception Tradeoff in Finite Channels with Arbitrary Distortion Measures”, ISIT 2024, and InfoCog workshop, NeurIPS 2023.

A. Kobovich, E. Yaakobi, and N. Weinberger, M-DAB: An Input-Distribution Optimization Algorithm for Composite DNA Storage by the Multinomial Channel, IZS 2024. 

M. Dikshtein, N. Weinberger, and S. Shamai (Shitz), “On Mismatched Oblivious Relaying”, ISIT 2023 (extended version).

N. Weinberger and M. Feder, "Misspecified Regret Rates of Convergence for Unknown Feature Density," ITW 2022 (Invited talk). 

M. Dikshtein, N. Weinberger, and S. Shamai (Shitz), "On Information Bottleneck for Gaussian Processes," ITW 2022.  

N. Weinberger and M. Feder, “On Information-Theoretic Determination of Misspecified Rates of Convergence,” ISIT 2022. 

N. Weinberger, Y. Kochman, and M. Wigger, “Exponent Trade-off for Hypothesis Testing Over Noisy Channels,”  ISIT 2019.

N. Weinberger and M. Feder, “Universal Decoding over Gaussian Fading Channels - Metric Calculation and Performance Evaluation,” ISIT 2011.

N. Weinberger and M. Feder, “Universal Decoding for Linear Gaussian Fading Channels in the Competitive Minimax Sense,” ISIT 2008.