All problems
92 problems. Tags (MAIS-O…) are permanent and never change, even if a title does.
| Tag | Title | Agenda | Fields | Diff. | Status |
|---|---|---|---|---|---|
| MAIS-O1 | Quantitative bounded LöbAgenda: A1Fields: logic, complexity theory | A1 | logic, complexity theory | ★★★ | open |
| MAIS-O2 | Recovering world-models from behaviorAgenda: A2Fields: statistics, probability, complexity theory | A2 | statistics, probability, complexity theory | ★★☆ | open |
| MAIS-O3 | The geometry and identifiability of superpositionAgenda: A3Fields: statistics, optimization, probability | A3 | statistics, optimization, probability | ★★★ | open |
| MAIS-O4 | Training for interpretabilityAgenda: A4Fields: optimization, convex geometry, probability | A4 | optimization, convex geometry, probability | ★★★ | open |
| MAIS-O5 | Representation theory of learned circuitsAgenda: A5Fields: dynamical systems, probability, representation theory | A5 | dynamical systems, probability, representation theory | ★★★ | open |
| MAIS-O6 | Does geometric simplicity force a legible mechanism?Agenda: A6Fields: algebraic geometry, harmonic analysis | A6 | algebraic geometry, harmonic analysis | ★★★ | open |
| MAIS-O7 | Opposing staircasesAgenda: A7Fields: algebraic geometry | A7 | algebraic geometry | ★★☆ | open |
| MAIS-O8 | A predictive theory of out-of-distribution generalizationAgenda: A8Fields: probability, optimization, dynamical systems | A8 | probability, optimization, dynamical systems | ★★★ | open |
| MAIS-O9 | Steering Conway's Life from a small seedAgenda: –Fields: probability, dynamical systems, complexity theory | – | probability, dynamical systems, complexity theory | ★★★ | open |
| MAIS-O10 | Polynomial overhead for Löb's theoremAgenda: A1Fields: logic, complexity theory | A1 | logic, complexity theory | ★★☆ | open |
| MAIS-O11 | Does Löb's rule shorten proofs?Agenda: A1Fields: logic, complexity theory | A1 | logic, complexity theory | ★★★ | open |
| MAIS-O12 | Expansion and diagonalization costs in Peano arithmeticAgenda: A1Fields: logic, complexity theory | A1 | logic, complexity theory | ★★☆ | open |
| MAIS-O13 | Provable comparisons between exp-log terms in arithmeticAgenda: A1Fields: logic | A1 | logic | ★★☆ | open |
| MAIS-O14 | Bounded Löb at logarithmic proof budgetsAgenda: A1Fields: logic | A1 | logic | ★★★ | open |
| MAIS-O15 | Explicit thresholds in parametric bounded LöbAgenda: A1Fields: logic, complexity theory | A1 | logic, complexity theory | ★★☆ | open |
| MAIS-O16 | The FairBot cooperation thresholdAgenda: A1Fields: logic, computational | A1 | logic, computational | ★★☆ | open |
| MAIS-O17 | Cooperation thresholds over families of bounded agentsAgenda: A1Fields: logic, complexity theory | A1 | logic, complexity theory | ★★☆ | open |
| MAIS-O18 | Admissible budgets for a bounded Löb axiomAgenda: A1Fields: logic | A1 | logic | ★★★ | open |
| MAIS-O19 | Soundness of Gödel–Löb logic under polynomial budgetsAgenda: A1Fields: logic | A1 | logic | ★★★ | open |
| MAIS-O20 | A bounded Payor lemma and its cooperation thresholdAgenda: A1Fields: logic | A1 | logic | ★★☆ | open |
| MAIS-O21 | Is the Löb overhead invariant under polynomial simulation?Agenda: A1Fields: logic, complexity theory | A1 | logic, complexity theory | ★★☆ | open |
| MAIS-O22 | A bounded analogue of Solovay's completeness theoremAgenda: A1Fields: logic | A1 | logic | ★★★ | open |
| MAIS-O23 | Do margins imply behavioral identifiability of causal models?Agenda: A2Fields: algebraic geometry, probability | A2 | algebraic geometry, probability | ★★★ | open |
| MAIS-O24 | Explicit polynomial margins replacing generic causal identifiabilityAgenda: A2Fields: algebraic geometry, probability, complexity theory | A2 | algebraic geometry, probability, complexity theory | ★★☆ | open |
| MAIS-O25 | Query complexity of causal model extraction from optimal policiesAgenda: A2Fields: complexity theory, statistics | A2 | complexity theory, statistics | ★★☆ | open |
| MAIS-O26 | Bisection attains optimal query complexity for causal model extractionAgenda: A2Fields: complexity theory, statistics | A2 | complexity theory, statistics | ★★☆ | open |
| MAIS-O27 | How agent regret limits causal model identifiabilityAgenda: A2Fields: statistics, probability | A2 | statistics, probability | ★★★ | open |
| MAIS-O28 | Causal model identifiability under average-case regretAgenda: A2Fields: probability, statistics | A2 | probability, statistics | ★★☆ | open |
| MAIS-O29 | Estimation rates and query design for Boltzmann agentsAgenda: A2Fields: statistics, optimization | A2 | statistics, optimization | ★★☆ | open |
| MAIS-O30 | Which interventions identify which parts of the causal graph?Agenda: A2Fields: combinatorics, probability | A2 | combinatorics, probability | ★★★ | open |
| MAIS-O31 | What one intervenable variable reveals about a causal chainAgenda: A2Fields: probability | A2 | probability | ★★☆ | open |
| MAIS-O32 | Tightness of the 1/n rate for depth-n goal agentsAgenda: A2Fields: probability, combinatorics | A2 | probability, combinatorics | ★★☆ | open |
| MAIS-O33 | Tolerable corruption fraction for goal-based model extractionAgenda: A2Fields: complexity theory, combinatorics, probability | A2 | complexity theory, combinatorics, probability | ★★★ | open |
| MAIS-O34 | Exact identified set for two-variable causal modelsAgenda: A2Fields: algebraic geometry, computational | A2 | algebraic geometry, computational | ★☆☆ | open |
| MAIS-O35 | Finite-sample recovery of two-variable causal modelsAgenda: A2Fields: statistics, probability | A2 | statistics, probability | ★☆☆ | open |
| MAIS-O36 | Global ℓ¹ dictionary recovery under independent supportsAgenda: A3Fields: probability, optimization, statistics | A3 | probability, optimization, statistics | ★★★ | open |
| MAIS-O37 | Two smeared features: recover, merge, or splitAgenda: A3Fields: optimization, probability, convex geometry | A3 | optimization, probability, convex geometry | ★★★ | open |
| MAIS-O38 | Polynomial sample complexity for dictionary uniqueness with growing sparsityAgenda: A3Fields: combinatorics, statistics | A3 | combinatorics, statistics | ★★★ | open |
| MAIS-O39 | Does the amortized encoder change the learned dictionary?Agenda: A3Fields: optimization, statistics | A3 | optimization, statistics | ★★★ | open |
| MAIS-O40 | Regular pentagon as global minimizer of a ReLU autoencoderAgenda: A3Fields: optimization, harmonic analysis | A3 | optimization, harmonic analysis | ★★★ | open |
| MAIS-O41 | Two-feature phase diagram for ℓ¹ dictionary learningAgenda: A3Fields: optimization, convex geometry | A3 | optimization, convex geometry | ★☆☆ | open |
| MAIS-O42 | Pentagon optimality for a pure ReLU packing energyAgenda: A3Fields: optimization, harmonic analysis | A3 | optimization, harmonic analysis | ★★☆ | open |
| MAIS-O43 | Measure the sparse-autoencoder recovery–merging phase diagramAgenda: A3Fields: computational, statistics | A3 | computational, statistics | ★☆☆ | open |
| MAIS-O44 | Does penalizing average interference lower coherence?Agenda: A4Fields: optimization, harmonic analysis, probability | A4 | optimization, harmonic analysis, probability | ★★☆ | open |
| MAIS-O45 | Does penalizing interference make features recoverable by dictionary learning?Agenda: A4Fields: statistics, optimization, probability | A4 | statistics, optimization, probability | ★★☆ | open |
| MAIS-O46 | Does lower coherence imply better dictionary recovery?Agenda: A4Fields: statistics, harmonic analysis | A4 | statistics, harmonic analysis | ★★☆ | open |
| MAIS-O47 | Uniqueness of ReLU toy-model minimizers up to symmetryAgenda: A4Fields: optimization, convex geometry | A4 | optimization, convex geometry | ★★★ | open |
| MAIS-O48 | Loss frontier for neuron-feature alignment under a bottleneckAgenda: A4Fields: optimization, probability | A4 | optimization, probability | ★★☆ | open |
| MAIS-O49 | Exact cost of weight sparsity in the ReLU toy modelAgenda: A4Fields: optimization, probability, combinatorics | A4 | optimization, probability, combinatorics | ★★☆ | open |
| MAIS-O50 | Which minima does gradient flow select from random initialization?Agenda: A4Fields: dynamical systems, probability, optimization | A4 | dynamical systems, probability, optimization | ★★★ | open |
| MAIS-O51 | The regularized phase diagram of the smallest modelAgenda: A4Fields: optimization, probability | A4 | optimization, probability | ★☆☆ | open |
| MAIS-O52 | How many Fourier frequencies do modular-addition networks use?Agenda: A5Fields: probability, dynamical systems, harmonic analysis | A5 | probability, dynamical systems, harmonic analysis | ★★★ | open |
| MAIS-O53 | Law of large numbers for neuron representation multiplicitiesAgenda: A5Fields: probability, representation theory, dynamical systems | A5 | probability, representation theory, dynamical systems | ★★★ | open |
| MAIS-O54 | Are selection probabilities proportional to squared representation dimension?Agenda: A5Fields: representation theory, probability | A5 | representation theory, probability | ★★★ | open |
| MAIS-O55 | Neuron purity and representation selection for S_3 networksAgenda: A5Fields: dynamical systems, representation theory, probability | A5 | dynamical systems, representation theory, probability | ★★★ | open |
| MAIS-O56 | Vanishing weight decay selects both S_3 representationsAgenda: A5Fields: dynamical systems, representation theory, optimization | A5 | dynamical systems, representation theory, optimization | ★★★ | open |
| MAIS-O57 | Does gradient flow on S_5 select randomly among representation sets?Agenda: A5Fields: probability, dynamical systems, representation theory | A5 | probability, dynamical systems, representation theory | ★★★ | open |
| MAIS-O58 | Exchangeability of learned frequencies beyond multiplicative symmetryAgenda: A5Fields: probability, harmonic analysis, dynamical systems | A5 | probability, harmonic analysis, dynamical systems | ★★★ | open |
| MAIS-O59 | Two neurons learning mod-5 addition: which frequencies win?Agenda: A5Fields: dynamical systems, probability, harmonic analysis | A5 | dynamical systems, probability, harmonic analysis | ★★☆ | open |
| MAIS-O60 | Does a single ReLU neuron align to one frequency?Agenda: A5Fields: dynamical systems, probability, harmonic analysis | A5 | dynamical systems, probability, harmonic analysis | ★★☆ | resolved |
| MAIS-O61 | Pilot measurement of representation selection in small trained networksAgenda: A5Fields: computational, statistics | A5 | computational, statistics | ★☆☆ | open |
| MAIS-O62 | Minimal network width for exact modular additionAgenda: A6Fields: complexity theory, algebraic geometry, harmonic analysis | A6 | complexity theory, algebraic geometry, harmonic analysis | ★★☆ | open |
| MAIS-O63 | Learning coefficients of modular additionAgenda: A6Fields: algebraic geometry, statistics | A6 | algebraic geometry, statistics | ★★★ | open |
| MAIS-O64 | Marginal cost of width for modular-addition networksAgenda: A6Fields: algebraic geometry, statistics | A6 | algebraic geometry, statistics | ★★★ | open |
| MAIS-O65 | Learning coefficients of modular addition under cross-entropyAgenda: A6Fields: algebraic geometry, statistics | A6 | algebraic geometry, statistics | ★★★ | open |
| MAIS-O66 | Generic constancy of learning coefficients over attention teachersAgenda: A6Fields: algebraic geometry, statistics | A6 | algebraic geometry, statistics | ★★★ | open |
| MAIS-O67 | Learning coefficients of one-head softmax attentionAgenda: A6Fields: algebraic geometry, statistics | A6 | algebraic geometry, statistics | ★★★ | open |
| MAIS-O68 | Learning coefficients of linear attentionAgenda: A6Fields: algebraic geometry, statistics, computational | A6 | algebraic geometry, statistics, computational | ★★☆ | open |
| MAIS-O69 | When does the localized posterior estimate the local learning coefficient?Agenda: A6Fields: statistics, probability | A6 | statistics, probability | ★★☆ | open |
| MAIS-O70 | Local learning coefficients of reduced-rank regressionAgenda: A6Fields: algebraic geometry, statistics | A6 | algebraic geometry, statistics | ★★☆ | open |
| MAIS-O71 | Free energy asymptotics for continuous-input ReLU networksAgenda: A6Fields: algebraic geometry, probability, statistics | A6 | algebraic geometry, probability, statistics | ★★★ | open |
| MAIS-O72 | Finiteness and frontier condition for learning-coefficient strataAgenda: A7Fields: algebraic geometry | A7 | algebraic geometry | ★★★ | open |
| MAIS-O73 | Eyring–Kramers law for singular wellsAgenda: A7Fields: probability, algebraic geometry | A7 | probability, algebraic geometry | ★★★ | open |
| MAIS-O74 | Eyring–Kramers prefactor for a singular well and Morse gateAgenda: A7Fields: probability, algebraic geometry | A7 | probability, algebraic geometry | ★★☆ | open |
| MAIS-O75 | Entropic selection between two flat strata on the torusAgenda: A7Fields: probability | A7 | probability | ★★☆ | open |
| MAIS-O76 | SGD limit diffusions on a singular set of minimizersAgenda: A7Fields: probability, algebraic geometry | A7 | probability, algebraic geometry | ★★★ | open |
| MAIS-O77 | Learning coefficients on the matrix factorization fiber and saddlesAgenda: A7Fields: algebraic geometry | A7 | algebraic geometry | ★★☆ | open |
| MAIS-O78 | A time-sample correspondence for the deep linear networkAgenda: A7Fields: statistics, probability | A7 | statistics, probability | ★★★ | open |
| MAIS-O79 | Saddles as effective minima under coarse-grainingAgenda: A7Fields: dynamical systems, algebraic geometry | A7 | dynamical systems, algebraic geometry | ★★★ | open |
| MAIS-O80 | Is leap complexity determined by singularity data?Agenda: A7Fields: algebraic geometry, combinatorics | A7 | algebraic geometry, combinatorics | ★★★ | open |
| MAIS-O81 | Does a saddle have a well-defined free energy?Agenda: A7Fields: statistics, algebraic geometry | A7 | statistics, algebraic geometry | ★★★ | open |
| MAIS-O82 | Wide networks select the proxy policy with probability oneAgenda: A8Fields: probability, optimization | A8 | probability, optimization | ★★★ | open |
| MAIS-O83 | Does some finite-width network favor the intended goal?Agenda: A8Fields: probability, optimization | A8 | probability, optimization | ★★★ | open |
| MAIS-O84 | The crossover time and its asymptoticsAgenda: A8Fields: dynamical systems, optimization, probability | A8 | dynamical systems, optimization, probability | ★★★ | open |
| MAIS-O85 | Which feature maps make the max-margin classifier misgeneralize?Agenda: A8Fields: convex geometry, optimization | A8 | convex geometry, optimization | ★★☆ | open |
| MAIS-O86 | Does gradient descent match the Gaussian process posterior?Agenda: A8Fields: probability, statistics | A8 | probability, statistics | ★★★ | open |
| MAIS-O87 | Does policy gradient stay misgeneralized despite training diversity?Agenda: A8Fields: dynamical systems, probability | A8 | dynamical systems, probability | ★★☆ | open |
| MAIS-O88 | Misgeneralization versus diversity for reinforcement learningAgenda: A8Fields: probability, dynamical systems | A8 | probability, dynamical systems | ★★★ | open |
| MAIS-O89 | Boundary-state residual of max-margin gradient descentAgenda: A8Fields: optimization, dynamical systems | A8 | optimization, dynamical systems | ★☆☆ | open |
| MAIS-O90 | Does finite-width training inherit the kernel flow's selection?Agenda: A8Fields: probability, optimization | A8 | probability, optimization | ★★☆ | open |
| MAIS-O91 | Numerical atlas of misgeneralization across widths and diversityAgenda: A8Fields: computational, probability | A8 | computational, probability | ★☆☆ | open |
| MAIS-O92 | The outcome law of one rectifier neuronAgenda: A5Fields: dynamical systems, probability, harmonic analysis | A5 | dynamical systems, probability, harmonic analysis | ★★★ | open |