---
title: "Nature Machine Intelligence 2024 — all accepted papers, page 2"
description: "All 178 papers of Nature Machine Intelligence 2024 · page 2 of 2, the most cited first; those with our summary link to it."
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# Nature Machine Intelligence 2024: all accepted papers

178 papers · page 2 of 2 · the most cited first · [← Nature Machine Intelligence 2024](https://md.research.elamur.ai/free/en/venues/nature-machine-intelligence/2024/)

[← prev](https://md.research.elamur.ai/free/en/venues/nature-machine-intelligence/2024/papers/) [1](https://md.research.elamur.ai/free/en/venues/nature-machine-intelligence/2024/papers/) **2**

101. **[Leveraging ancestral sequence reconstruction for protein representation learning ↗](https://doi.org/10.1038/s42256-024-00935-2)**Dana S. Matthews, Matthew A. Spence, Adam C. Mater et al.*20 citations*
102. **[Nanobody–antigen interaction prediction with ensemble deep learning and prompt-based protein language models ↗](https://doi.org/10.1038/s42256-024-00940-5)**Juntao Deng, Miao Gu, Pengyan Zhang et al.*20 citations*
103. **[Unsupervised learning of topological non-Abelian braiding in non-Hermitian bands ↗](https://doi.org/10.1038/s42256-024-00871-1)**Yang Long, Haoran Xue, Baile Zhang*20 citations*
104. **[Zero-shot transfer of protein sequence likelihood models to thermostability prediction ↗](https://doi.org/10.1038/s42256-024-00887-7)**Shawn Reeves, Subha Kalyaanamoorthy*19 citations*
105. **[Improving generalization of machine learning-identified biomarkers using causal modelling with examples from immune receptor diagnostics ↗](https://doi.org/10.1038/s42256-023-00781-8)**Milena Pavlović, Ghadi S. Al Hajj, Chakravarthi Kanduri et al.*17 citations*
106. **[Sparse learned kernels for interpretable and efficient medical time series processing ↗](https://doi.org/10.1038/s42256-024-00898-4)**Sully F. Chen, Zhicheng Guo, Cheng Ding et al.*17 citations*
107. **[Discussions of machine versus living intelligence need more clarity ↗](https://doi.org/10.1038/s42256-024-00955-y)**Nicolas Rouleau, Michael G. Levin*16 citations*
108. **[Learning efficient backprojections across cortical hierarchies in real time ↗](https://doi.org/10.1038/s42256-024-00845-3)**Kevin Max, Laura Kriener, Garibaldi Pineda García et al.*16 citations*
109. **[Mitigating allocative tradeoffs and harms in an environmental justice data tool ↗](https://doi.org/10.1038/s42256-024-00793-y)**Benjamin Q. Huynh, Elizabeth T. Chin, Allison Koenecke et al.*16 citations*
110. **[Discovering neural policies to drive behaviour by integrating deep reinforcement learning agents with biological neural networks ↗](https://doi.org/10.1038/s42256-024-00854-2)**Chenguang Li, Gabriel Kreiman, Sharad Ramanathan*14 citations*
111. **[The curious case of the test set AUROC ↗](https://doi.org/10.1038/s42256-024-00817-7)**Michael T. Roberts, Alon Hazan, Sören Dittmer et al.*14 citations*
112. **[The democratization of global AI governance and the role of tech companies ↗](https://doi.org/10.1038/s42256-024-00811-z)**Eva Erman, Markus Furendal*14 citations*
113. **[Variational autoencoder for design of synthetic viral vector serotypes ↗](https://doi.org/10.1038/s42256-023-00787-2)**Suyue Lyu, Shahin Sowlati‐Hashjin, Michael Garton*14 citations*
114. **[Efficient rare event sampling with unsupervised normalizing flows ↗](https://doi.org/10.1038/s42256-024-00918-3)**Solomon Asghar, Qing‐Xiang Pei, Giorgio Volpe et al.*13 citations*
115. **[The new NeuroAI ↗](https://doi.org/10.1038/s42256-024-00826-6)***13 citations*
116. **[Anniversary AI reflections ↗](https://doi.org/10.1038/s42256-023-00784-5)**Noelia Ferruz, Marinka Žitnik, Pierre‐Yves Oudeyer et al.*12 citations*
117. **[Connecting molecular properties with plain language ↗](https://doi.org/10.1038/s42256-024-00812-y)**Glen M. Hocky*12 citations*
118. **[The need for reproducible research in soft robotics ↗](https://doi.org/10.1038/s42256-024-00869-9)**Robert L. Baines, Dylan Shah, Jeremy A. Marvel et al.*12 citations*
119. **[Data-driven discovery of movement-linked heterogeneity in neurodegenerative diseases ↗](https://doi.org/10.1038/s42256-024-00882-y)**Mark Endo, Favour Nerrise, Qingyu Zhao et al.*11 citations*
120. **[Deep learning prediction of ribosome profiling with Translatomer reveals translational regulation and interprets disease variants ↗](https://doi.org/10.1038/s42256-024-00915-6)**Jialin He, Lei Xiong, Shaohui Shi et al.*11 citations*
121. **[Engineering flexible machine learning systems by traversing functionally invariant paths ↗](https://doi.org/10.1038/s42256-024-00902-x)**Guruprasad Raghavan, Bahey Tharwat, Surya N. Hari et al.*11 citations*
122. **[Modulating emotional states of rats through a rat-like robot with learned interaction patterns ↗](https://doi.org/10.1038/s42256-024-00939-y)**Guanglu Jia, Zhe Chen, Yulai Zhang et al.*11 citations*
123. **[Partial-convolution-implemented generative adversarial network for global oceanic data assimilation ↗](https://doi.org/10.1038/s42256-024-00867-x)**Yoo‐Geun Ham, Yong-Sik Joo, Jeong-Hwan Kim et al.*11 citations*
124. **[Reusability report: Uncovering associations in biomedical bipartite networks via a bilinear attention network with domain adaptation ↗](https://doi.org/10.1038/s42256-024-00822-w)**Tao Xu, Haoyuan Shi, Wanling Gao et al.*11 citations*
125. **[Reusability report: exploring the utility of variational graph encoders for predicting molecular toxicity in drug design ↗](https://doi.org/10.1038/s42256-024-00923-6)**Ruijiang Li, Jiang Lu, Ziyi Liu et al.*11 citations*
126. **[The synergy complement control approach for seamless limb-driven prostheses ↗](https://doi.org/10.1038/s42256-024-00825-7)**Johannes Kühn, Tingli Hu, Alexander Toedtheide et al.*11 citations*
127. **[Visual odometry with neuromorphic resonator networks ↗](https://doi.org/10.1038/s42256-024-00846-2)**Alpha Renner, Lazar Supic, Andreea Danielescu et al.*10 citations*
128. **[A multi-modal deep language model for contaminant removal from metagenome-assembled genomes ↗](https://doi.org/10.1038/s42256-024-00908-5)**Bohao Zou, Jingjing Wang, Yi Ding et al.*9 citations*
129. **[AI in biomaterials discovery: generating self-assembling peptides with resource-efficient deep learning ↗](https://doi.org/10.1038/s42256-024-00936-1)**Tianang Leng, César de la Fuente‐Núñez*9 citations*
130. **[Empathic AI can’t get under the skin ↗](https://doi.org/10.1038/s42256-024-00850-6)***9 citations*
131. **[Generating mutants of monotone affinity towards stronger protein complexes through adversarial learning ↗](https://doi.org/10.1038/s42256-024-00803-z)**Tian Lan, Shuquan Su, Pengyao Ping et al.*9 citations*
132. **[Is it five already? ↗](https://doi.org/10.1038/s42256-024-00796-9)***9 citations*
133. **[Realizing full-body control of humanoid robots ↗](https://doi.org/10.1038/s42256-024-00891-x)**Guangliang Li, Randy Gómez*9 citations*
134. **[AI pioneers win 2024 Nobel prizes ↗](https://doi.org/10.1038/s42256-024-00945-0)***8 citations*
135. **[Estimation of causal effects of genes on complex traits using a Bayesian-network-based framework applied to GWAS data ↗](https://doi.org/10.1038/s42256-024-00906-7)**Liangying Yin, Yaning Feng, Yujia Shi et al.*8 citations*
136. **[High-resolution real-space reconstruction of cryo-EM structures using a neural field network ↗](https://doi.org/10.1038/s42256-024-00870-2)**Yue Hui Huang, Chengguang Zhu, Xiaokang Yang et al.*8 citations*
137. **[Successful implementation of the EU AI Act requires interdisciplinary efforts ↗](https://doi.org/10.1038/s42256-024-00954-z)**Christian Montag, Michèle Finck*8 citations*
138. **[Will generative AI transform robotics? ↗](https://doi.org/10.1038/s42256-024-00862-2)***8 citations*
139. **[An interpretable deep learning framework for genome-informed precision oncology ↗](https://doi.org/10.1038/s42256-024-00866-y)**Shuangxia Ren, Gregory F. Cooper, Lujia Chen et al.*7 citations*
140. **[Diving into deep learning ↗](https://doi.org/10.1038/s42256-024-00840-8)**Ge Wang*7 citations*
141. **[Foundation models in healthcare require rethinking reliability ↗](https://doi.org/10.1038/s42256-024-00924-5)**Thomas Grote, Timo Freiesleben, Philipp Berens*7 citations*
142. **[Limitations in odour recognition and generalization in a neuromorphic olfactory circuit ↗](https://doi.org/10.1038/s42256-024-00952-1)**Nik Dennler, van Schaik André, Michael Schmuker*7 citations*
143. **[What comparing deep neural networks can teach us about human vision ↗](https://doi.org/10.1038/s42256-024-00789-8)**Katja Seeliger, Martin N. Hebart*7 citations*
144. **[What is in your LLM-based framework? ↗](https://doi.org/10.1038/s42256-024-00896-6)***7 citations*
145. **[Back to basics to open the black box ↗](https://doi.org/10.1038/s42256-024-00842-6)**Diego Marcondes, Adilson Simonis, Júnior Barrera*6 citations*
146. **[Fast and generalizable micromagnetic simulation with deep neural nets ↗](https://doi.org/10.1038/s42256-024-00914-7)**Yunqi Cai, Jiangnan Li, Dong Wang*6 citations*
147. **[Inversion dynamics of class manifolds in deep learning reveals tradeoffs underlying generalization ↗](https://doi.org/10.1038/s42256-023-00772-9)**Simone Ciceri, Lorenzo Cassani, Matteo Osella et al.*6 citations*
148. **[Reusability report: Unpaired deep-learning approaches for holographic image reconstruction ↗](https://doi.org/10.1038/s42256-024-00798-7)**Yuhe Zhang, Tobias Ritschel, Pablo Villanueva‐Perez*6 citations*
149. **[Sequential memory improves sample and memory efficiency in episodic control ↗](https://doi.org/10.1038/s42256-024-00950-3)**Ismael T. Freire, Adrián F. Amil, Paul F. M. J. Verschure*6 citations*
150. **[Envisioning better benchmarks for machine learning PDE solvers ↗](https://doi.org/10.1038/s42256-024-00962-z)**J. Brandstetter*5 citations*
151. **[Lessons from a challenge on forecasting epileptic seizures from non-cerebral signals ↗](https://doi.org/10.1038/s42256-024-00799-6)**Kenny Schlegel, Denis V. Kleyko, Benjamin H. Brinkmann et al.*5 citations*
152. **[Self-decoupling three-axis forces in a simple sensor ↗](https://doi.org/10.1038/s42256-024-00941-4)**Kuanming Yao, Qiuna Zhuang*5 citations*
153. **[A plea for caution and guidance about using AI in genomics ↗](https://doi.org/10.1038/s42256-024-00947-y)**Mohammad Hosseini, Christopher Donohue*4 citations*
154. **[ARNLE model identifies prevalence potential of SARS-CoV-2 variants ↗](https://doi.org/10.1038/s42256-024-00919-2)**Yuqi Liu, Jing Li, Peihan Li et al.*4 citations*
155. **[Advanced AI assistants that act on our behalf may not be ethically or legally feasible ↗](https://doi.org/10.1038/s42256-024-00877-9)**Silvia Milano, Sven Nyholm*4 citations*
156. **[Artificial intelligence tackles the nature–nurture debate ↗](https://doi.org/10.1038/s42256-024-00828-4)**Justin N. Wood*4 citations*
157. **[Deep learning at the forefront of detecting tipping points ↗](https://doi.org/10.1038/s42256-024-00957-w)**Smita Deb, Partha Sharathi Dutta*4 citations*
158. **[Kernel approximation using analogue in-memory computing ↗](https://doi.org/10.1038/s42256-024-00943-2)**Julian Büchel, Giacomo Camposampiero, Athanasios Vasilopoulos et al.*4 citations*
159. **[Reusability report: Annotating metabolite mass spectra with domain-inspired chemical formula transformers ↗](https://doi.org/10.1038/s42256-024-00909-4)**Janne Heirman, Wout Bittremieux*4 citations*
160. **[Reusability report: Leveraging supervised learning to uncover phenotype-relevant biology from single-cell RNA sequencing data ↗](https://doi.org/10.1038/s42256-024-00804-y)**Yingying Cao, Tiangen Chang, Sahil Sahni et al.*4 citations*
161. **[The rewards of reusable machine learning code ↗](https://doi.org/10.1038/s42256-024-00835-5)***4 citations*
162. **[Dangers of speech technology for workplace diversity ↗](https://doi.org/10.1038/s42256-024-00827-5)**Mike Horia Teodorescu, Mingang K. Geiger, Lily Morse*3 citations*
163. **[Towards a personalized AI assistant to learn machine learning ↗](https://doi.org/10.1038/s42256-024-00953-0)**Pascal Wallisch, Ibrahim Sheikh*3 citations*
164. **[AI protein shake-up ↗](https://doi.org/10.1038/s42256-024-00806-w)***2 citations*
165. **[An end-to-end recurrent compressed sensing method to denoise, detect and demix calcium imaging data ↗](http://dx.doi.org/10.1038/s42256-024-00892-w)**Kangning Zhang, Sean Tang, Vivian Zhu et al.*2 citations*
166. **[Cognitive maps from predictive vision ↗](https://doi.org/10.1038/s42256-024-00885-9)**Margaret von Ebers, Xue-Xin Wei*2 citations*
167. **[Pick your AI poison ↗](https://doi.org/10.1038/s42256-024-00921-8)***2 citations*
168. **[Reply to: Deeper evaluation of a single-cell foundation model ↗](https://doi.org/10.1038/s42256-024-00948-x)**Fan Yang, Fang Wang, Long-Kai Huang et al.*2 citations*
169. **[Strategies needed to counter potential AI misuse ↗](https://doi.org/10.1038/s42256-024-00967-8)***2 citations*
170. **[A question of trust for AI research in medicine ↗](https://doi.org/10.1038/s42256-024-00880-0)***1 citation*
171. **[A step forward in tracing and documenting dataset provenance ↗](https://doi.org/10.1038/s42256-024-00884-w)**Nicholas Vincent*1 citation*
172. **[Guidelines for study protocols describing predefined validations of prediction models in medical deep learning and beyond ↗](https://doi.org/10.1038/s42256-023-00774-7)**Andreas Kleppe, Ole-Johan Skrede, Knut Liestøl et al.*1 citation*
173. **[Reply to: Limitations in odour recognition and generalization in a neuromorphic olfactory circuit ↗](https://doi.org/10.1038/s42256-024-00951-2)**Roy Moyal, Nabil Imam, Thomas A. Cleland*1 citation*
174. **[Seeking clarity rather than strong opinions on intelligence ↗](https://doi.org/10.1038/s42256-024-00968-7)***1 citation*
175. **[Shielding sensitive medical imaging data ↗](https://doi.org/10.1038/s42256-024-00865-z)**Gaoyang Liu, Chen Wang, Tian Xia*1 citation*
176. **[A multiscale approach for biomedical machine learning ↗](https://doi.org/10.1038/s42256-024-00907-6)**
177. **[Clinical large language models with misplaced focus ↗](https://doi.org/10.1038/s42256-024-00929-0)**Zining Luo, Haowei Ma, Zhiwu Li et al.
178. **[Memetic robots ↗](https://doi.org/10.1038/s42256-024-00959-8)**Thomas Schmickl

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