*ICLR 2025 <https://iclr.cc/> Workshop: I Can’t Believe It’s Not Better: Challenges in Applied Deep Learning* *Call for Papers: *This workshop focuses on negative results, failed experiments, and unexpected challenges encountered when applying deep learning to real-world problems across industry and science. By openly sharing these hurdles, we aim to advance the field through transparency, foster learning, and prevent repeated missteps. *We welcome submissions* that apply deep learning to various domains including, but not limited to, neuroscience, healthcare, psychology and feature: 1. A real-world use case where deep learning was applied. 2. An existing deep learning solution proposed in the literature. 3. An observed negative or unexpected outcome. 4. An analysis of why the approach did not work as anticipated. Possible reasons may include data issues, model assumptions, interpretability gaps, scalability challenges, or deployment constraints. Submissions will be evaluated based on rigor, novelty, clarity, reproducibility, and the depth of their insights. *Key Dates:* • Submission Deadline: February 3, 2025 (11:59 pm AOE) • Acceptance Notification: March 5, 2025 • Workshop: April 27 or 28, 2025 Accepted papers will appear on OpenReview and the workshop website, with the option for inclusion in PMLR proceedings <https://proceedings.mlr.press/>. We will also nominate outstanding submissions for spotlight talks and two awards: the “Entropic Award” for the most surprising negative result and the “Didactic Award” for the most pedagogically valuable paper. For more information on our past workshops, the ICBINB initiative, and submission details, please visit: https://sites.google.com/view/icbinb-2025/call-for-papers We look forward to your contributions! Sincerely, The I Can’t Believe It’s Not Better Organizing Team